Timezone: »
Since we are a small workshop, we will hold the poster sessions during the day, including all the breaks as the authors wish.
Author Information
Xingyou Song (Google Brain)
Elad Hoffer (Technion)
Wei-Cheng Chang (Carnegie Mellon University)
Jeremy Cohen (Carnegie Mellon University)
Jyoti Islam (Georgia State University)
Yaniv Blumenfeld (Technion)
Andreas Madsen (Computationally Demanding)
Jonathan Frankle (MIT)
Sebastian Goldt (Institut de Physique Théorique, CNRS, Paris)
Satrajit Chatterjee (Google AI)
Abhishek Panigrahi (Microsoft Research India)
Alex Renda (MIT)
Brian Bartoldson (Florida State University)
Israel Birhane (Mila)
MSE Student , Programmer, Researcher and Robotics Architect
Aristide Baratin (Université de Montreal)
Niladri Chatterji (UC Berkeley)
Roman Novak (Google Brain)
Jessica Forde (Brown University)
YiDing Jiang (Google Research)
Yilun Du (MIT)
Linara Adilova (Fraunhofer IAIS)
Michael Kamp (Fraunhofer IAIS)
Berry Weinstein (IDC)
Itay Hubara (Technion)
Tal Ben-Nun (ETH Zurich)
Torsten Hoefler (ETH Zurich)
Daniel Soudry (Technion)
I am an assistant professor in the Department of Electrical Engineering at the Technion, working in the areas of Machine learning and theoretical neuroscience. I am especially interested in all aspects of neural networks and deep learning. I did my post-doc (as a Gruss Lipper fellow) working with Prof. Liam Paninski in the Department of Statistics, the Center for Theoretical Neuroscience the Grossman Center for Statistics of the Mind, the Kavli Institute for Brain Science, and the NeuroTechnology Center at Columbia University. I did my Ph.D. (2008-2013, direct track) in the Network Biology Research Laboratory in the Department of Electrical Engineering at the Technion, Israel Institute of technology, under the guidance of Prof. Ron Meir. In 2008 I graduated summa cum laude with a B.Sc. in Electrical Engineering and a B.Sc. in Physics, after studying in the Technion since 2004.
Hsiang-Fu Yu (Amazon)
Kai Zhong (Amazon)
Yiming Yang (CMU)
Inderjit Dhillon (UT Austin & Amazon)
Jaime Carbonell (CMU)
Yanqing Zhang (Georgia State University)
Dar Gilboa (Columbia University)
Johannes Brandstetter (LIT AI Lab / University Linz)
Alexander R Johansen (DTU)
Gintare Karolina Dziugaite (Element AI)
Raghav Somani (University of Washington)
Theoretical Machine Learning enthusiast majorly interested in Optimization and Statistics.
Ari Morcos (Facebook AI Research)
Freddie Kalaitzis (Element AI)

Freddie is a Senior Research Fellow at the Dept. of Computer Science, University of Oxford, investigating topics mainly in AI for Earth Observation. He is the principal investigator of OpenSR, a €1M government contract with ESA, to increase the safety of Super-Resolution technology for the Sentinel-2 archive. He is also an independent consultant, involved in projects where he leads teams in the Frontier Development Lab (FDL), a private-public partnership between NASA, SETI, and Trillium Technologies. His recent FDL projects were funded by NASA SMD to investigate the use of SAR imagery for disaster detection, and by the USGS to develop near-real-time water stream mapping from daily PlanetScope imagery. His most recent work is a survey on the State of AI for Earth Observation, in collaboration with Satellite Applications Catapult.
Hanie Sedghi (Google Brain)

I am a senior research scientist at Google Brain, where I lead the “Deep Phenomena” team. My approach is to bond theory and practice in large-scale machine learning by designing algorithms with theoretical guarantees that also work efficiently in practice. Over the recent years, I have been working on understanding and improving deep learning. Prior to Google, I was a Research Scientist at Allen Institute for Artificial Intelligence and before that, a postdoctoral fellow at UC Irvine. I received my PhD from University of Southern California with a minor in mathematics in 2015.
Lechao Xiao (Google Brain)
John Zech (Icahn School of Medicine)
Muqiao Yang (Carnegie Mellon University)
Simran Kaur (Carnegie Mellon University)
Qianli Ma (Carnegie Mellon University)
Yao-Hung Hubert Tsai (Carnegie Mellon University)
Ruslan Salakhutdinov (Carnegie Mellon University)
Sho Yaida (Facebook AI Research)
Zachary Lipton (Carnegie Mellon University)
Daniel Roy (Univ of Toronto & Vector)
Michael Carbin (MIT)
Florent Krzakala (École Normale Supérieure)
Lenka Zdeborová (CEA)
Guy Gur-Ari (Google)
Ethan Dyer (Google)
Dilip Krishnan (Google)
Hossein Mobahi (Google Research)
Samy Bengio (Google Research, Brain Team)
Behnam Neyshabur (New York University)
I am a staff research scientist at Google. Before that, I was a postdoctoral researcher at New York University and a member of Theoretical Machine Learning program at Institute for Advanced Study (IAS) in Princeton. In summer 2017, I received a PhD in computer science at TTI-Chicago where I was fortunate to be advised by Nati Srebro.
Praneeth Netrapalli (Microsoft Research)
Kris Sankaran (Mila)
Julien Cornebise (Element AI)
Yoshua Bengio (Mila)
Yoshua Bengio is Full Professor in the computer science and operations research department at U. Montreal, scientific director and founder of Mila and of IVADO, Turing Award 2018 recipient, Canada Research Chair in Statistical Learning Algorithms, as well as a Canada AI CIFAR Chair. He pioneered deep learning and has been getting the most citations per day in 2018 among all computer scientists, worldwide. He is an officer of the Order of Canada, member of the Royal Society of Canada, was awarded the Killam Prize, the Marie-Victorin Prize and the Radio-Canada Scientist of the year in 2017, and he is a member of the NeurIPS advisory board and co-founder of the ICLR conference, as well as program director of the CIFAR program on Learning in Machines and Brains. His goal is to contribute to uncover the principles giving rise to intelligence through learning, as well as favour the development of AI for the benefit of all.
Vincent Michalski (Université de Montréal)
Samira Ebrahimi Kahou (McGill University)
Md Rifat Arefin (University of Montreal)
Jiri Hron (University of Cambridge)
Jaehoon Lee (Google Brain)
Jascha Sohl-Dickstein (Google Brain)
Samuel Schoenholz (Google Brain)
David Schwab (ITS, CUNY Graduate Center)
Dongyu Li (Carnegie Mellon University)
Sang Choe (Carnegie Mellon University)
Henning Petzka (Lund University)
Ashish Verma (IBM Research)
Zhichao Lin (Element AI)
Cristian Sminchisescu (Google Research)
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Francois Charton · Noah Goodman · Behnam Neyshabur · Talia Ringer · Daniel Selsam -
2022 : Teaching Algorithmic Reasoning via In-context Learning »
Hattie Zhou · Azade Nova · aaron courville · Hugo Larochelle · Behnam Neyshabur · Hanie Sedghi -
2022 : Equivariance with Learned Canonical Mappings »
Oumar Kaba · Arnab Mondal · Yan Zhang · Yoshua Bengio · Siamak Ravanbakhsh -
2022 : Panel Discussion »
Behnam Neyshabur · David Sontag · Pradeep Ravikumar · Erin Hartman -
2022 : Length Generalization in Quantitative Reasoning »
Behnam Neyshabur -
2022 : Invited Keynote 1 »
Yoshua Bengio -
2022 Workshop: Machine Learning and the Physical Sciences »
Atilim Gunes Baydin · Adji Bousso Dieng · Emine Kucukbenli · Gilles Louppe · Siddharth Mishra-Sharma · Benjamin Nachman · Brian Nord · Savannah Thais · Anima Anandkumar · Kyle Cranmer · Lenka Zdeborová · Rianne van den Berg -
2022 : FL Games: A Federated Learning Framework for Distribution Shifts »
Sharut Gupta · Kartik Ahuja · Mohammad Havaei · Niladri Chatterjee · Yoshua Bengio -
2022 : Local Causal Discovery for Estimating Causal Effects »
Shantanu Gupta · David Childers · Zachary Lipton -
2022 : Panel Discussion »
Cheng Zhang · Mihaela van der Schaar · Ilya Shpitser · Aapo Hyvarinen · Yoshua Bengio · Bernhard Schölkopf -
2022 Workshop: AI for Science: Progress and Promises »
Yi Ding · Yuanqi Du · Tianfan Fu · Hanchen Wang · Anima Anandkumar · Yoshua Bengio · Anthony Gitter · Carla Gomes · Aviv Regev · Max Welling · Marinka Zitnik -
2022 Poster: Controlled Sparsity via Constrained Optimization or: How I Learned to Stop Tuning Penalties and Love Constraints »
Jose Gallego-Posada · Juan Ramirez · Akram Erraqabi · Yoshua Bengio · Simon Lacoste-Julien -
2022 Poster: Zero-shot Transfer Learning within a Heterogeneous Graph via Knowledge Transfer Networks »
Minji Yoon · John Palowitch · Dustin Zelle · Ziniu Hu · Ruslan Salakhutdinov · Bryan Perozzi -
2022 Poster: DIMES: A Differentiable Meta Solver for Combinatorial Optimization Problems »
Ruizhong Qiu · Zhiqing Sun · Yiming Yang -
2022 Poster: ENS-10: A Dataset For Post-Processing Ensemble Weather Forecasts »
Saleh Ashkboos · Langwen Huang · Nikoli Dryden · Tal Ben-Nun · Peter Dueben · Lukas Gianinazzi · Luca Kummer · Torsten Hoefler -
2022 Poster: MAgNet: Mesh Agnostic Neural PDE Solver »
Oussama Boussif · Yoshua Bengio · Loubna Benabbou · Dan Assouline -
2022 Poster: Lottery Tickets on a Data Diet: Finding Initializations with Sparse Trainable Networks »
Mansheej Paul · Brett Larsen · Surya Ganguli · Jonathan Frankle · Gintare Karolina Dziugaite -
2022 Poster: Neural Attentive Circuits »
Martin Weiss · Nasim Rahaman · Francesco Locatello · Chris Pal · Yoshua Bengio · Bernhard Schölkopf · Erran Li Li · Nicolas Ballas -
2022 Poster: Redundant representations help generalization in wide neural networks »
Diego Doimo · Aldo Glielmo · Sebastian Goldt · Alessandro Laio -
2022 Poster: Weakly Supervised Representation Learning with Sparse Perturbations »
Kartik Ahuja · Jason Hartford · Yoshua Bengio -
2022 Poster: Trajectory balance: Improved credit assignment in GFlowNets »
Nikolay Malkin · Moksh Jain · Emmanuel Bengio · Chen Sun · Yoshua Bengio -
2022 Poster: Paraphrasing Is All You Need for Novel Object Captioning »
Cheng-Fu Yang · Yao-Hung Hubert Tsai · Wan-Cyuan Fan · Russ Salakhutdinov · Louis-Philippe Morency · Frank Wang -
2022 Poster: Phase diagram of Stochastic Gradient Descent in high-dimensional two-layer neural networks »
Rodrigo Veiga · Ludovic Stephan · Bruno Loureiro · Florent Krzakala · Lenka Zdeborová -
2022 Poster: S3GC: Scalable Self-Supervised Graph Clustering »
Fnu Devvrit · Aditya Sinha · Inderjit Dhillon · Prateek Jain -
2022 Poster: ELIAS: End-to-End Learning to Index and Search in Large Output Spaces »
Nilesh Gupta · Patrick Chen · Hsiang-Fu Yu · Cho-Jui Hsieh · Inderjit Dhillon -
2022 Poster: Beyond neural scaling laws: beating power law scaling via data pruning »
Ben Sorscher · Robert Geirhos · Shashank Shekhar · Surya Ganguli · Ari Morcos -
2022 Poster: Evaluation beyond Task Performance: Analyzing Concepts in AlphaZero in Hex »
Charles Lovering · Jessica Forde · George Konidaris · Ellie Pavlick · Michael Littman -
2022 Poster: Towards Learning Universal Hyperparameter Optimizers with Transformers »
Yutian Chen · Xingyou Song · Chansoo Lee · Zi Wang · Richard Zhang · David Dohan · Kazuya Kawakami · Greg Kochanski · Arnaud Doucet · Marc'Aurelio Ranzato · Sagi Perel · Nando de Freitas -
2022 Poster: Subspace clustering in high-dimensions: Phase transitions & Statistical-to-Computational gap »
Luca Pesce · Bruno Loureiro · Florent Krzakala · Lenka Zdeborová -
2022 Poster: Open High-Resolution Satellite Imagery: The WorldStrat Dataset – With Application to Super-Resolution »
Julien Cornebise · Ivan Oršolić · Freddie Kalaitzis -
2022 Poster: Exploring Length Generalization in Large Language Models »
Cem Anil · Yuhuai Wu · Anders Andreassen · Aitor Lewkowycz · Vedant Misra · Vinay Ramasesh · Ambrose Slone · Guy Gur-Ari · Ethan Dyer · Behnam Neyshabur -
2022 Poster: Temporal Latent Bottleneck: Synthesis of Fast and Slow Processing Mechanisms in Sequence Learning »
Aniket Didolkar · Kshitij Gupta · Anirudh Goyal · Nitesh Bharadwaj Gundavarapu · Alex Lamb · Nan Rosemary Ke · Yoshua Bengio -
2022 Poster: Revisiting Neural Scaling Laws in Language and Vision »
Ibrahim Alabdulmohsin · Behnam Neyshabur · Xiaohua Zhai -
2022 Poster: Pruning’s Effect on Generalization Through the Lens of Training and Regularization »
Tian Jin · Michael Carbin · Dan Roy · Jonathan Frankle · Gintare Karolina Dziugaite -
2022 Poster: Spatial Mixture-of-Experts »
Nikoli Dryden · Torsten Hoefler -
2022 Poster: Multi-layer State Evolution Under Random Convolutional Design »
Max Daniels · Cedric Gerbelot · Florent Krzakala · Lenka Zdeborová -
2022 Poster: Solving Quantitative Reasoning Problems with Language Models »
Aitor Lewkowycz · Anders Andreassen · David Dohan · Ethan Dyer · Henryk Michalewski · Vinay Ramasesh · Ambrose Slone · Cem Anil · Imanol Schlag · Theo Gutman-Solo · Yuhuai Wu · Behnam Neyshabur · Guy Gur-Ari · Vedant Misra -
2022 Poster: Is a Modular Architecture Enough? »
Sarthak Mittal · Yoshua Bengio · Guillaume Lajoie -
2022 Poster: Fast Neural Kernel Embeddings for General Activations »
Insu Han · Amir Zandieh · Jaehoon Lee · Roman Novak · Lechao Xiao · Amin Karbasi -
2022 Poster: Learning Robust Dynamics through Variational Sparse Gating »
Arnav Kumar Jain · Shivakanth Sujit · Shruti Joshi · Vincent Michalski · Danijar Hafner · Samira Ebrahimi Kahou -
2022 Poster: Learning to Reason with Neural Networks: Generalization, Unseen Data and Boolean Measures »
Emmanuel Abbe · Samy Bengio · Elisabetta Cornacchia · Jon Kleinberg · Aryo Lotfi · Maithra Raghu · Chiyuan Zhang -
2022 Poster: Block-Recurrent Transformers »
DeLesley Hutchins · Imanol Schlag · Yuhuai Wu · Ethan Dyer · Behnam Neyshabur -
2022 : Keynote talk: A Deep Learning Journey »
Yoshua Bengio -
2021 : TD | Panel Discussion »
Thomas Gilbert · Ayse Yasar · Rachel Thomas · Mason Kortz · Frank Pasquale · Jessica Forde -
2021 : Live Q&A Session 2 with Susan Athey, Yoshua Bengio, Sujeeth Bharadwaj, Jane Wang, Joshua Vogelstein, Weiwei Yang »
Susan Athey · Yoshua Bengio · Sujeeth Bharadwaj · Jane Wang · Weiwei Yang · Joshua T Vogelstein -
2021 : Live Q&A Session 1 with Yoshua Bengio, Leyla Isik, Konrad Kording, Bernhard Scholkopf, Amit Sharma, Joshua Vogelstein, Weiwei Yang »
Yoshua Bengio · Leyla Isik · Konrad Kording · Bernhard Schölkopf · Joshua T Vogelstein · Weiwei Yang -
2021 Workshop: Tackling Climate Change with Machine Learning »
Maria João Sousa · Hari Prasanna Das · Sally Simone Fobi · Jan Drgona · Tegan Maharaj · Yoshua Bengio -
2021 : General Discussion 1 - What is out of distribution (OOD) generalization and why is it important? with Yoshua Bengio, Leyla Isik, Max Welling »
Yoshua Bengio · Leyla Isik · Max Welling · Joshua T Vogelstein · Weiwei Yang -
2021 : Is Importance Weighting Incompatible with Interpolating Classifiers? »
Ke Alexander Wang · Niladri Chatterji · Saminul Haque · Tatsunori Hashimoto -
2021 : AI X Discovery »
Yoshua Bengio -
2021 : Learning Neurosymbolic Performance Models »
Michael Carbin -
2021 : Panel Discussion 2 »
Susan L Epstein · Yoshua Bengio · Lucina Uddin · Rohan Paul · Steve Fleming -
2021 : Desiderata and ML Research Programme for Higher-Level Cognition »
Yoshua Bengio -
2021 : From model compression to self-distillation: a review »
Samira Ebrahimi Kahou -
2021 Workshop: Causal Inference & Machine Learning: Why now? »
Elias Bareinboim · Bernhard Schölkopf · Terrence Sejnowski · Yoshua Bengio · Judea Pearl -
2021 Workshop: Machine Learning and the Physical Sciences »
Anima Anandkumar · Kyle Cranmer · Mr. Prabhat · Lenka Zdeborová · Atilim Gunes Baydin · Juan Carrasquilla · Emine Kucukbenli · Gilles Louppe · Benjamin Nachman · Brian Nord · Savannah Thais -
2021 Workshop: I (Still) Can't Believe It's Not Better: A workshop for “beautiful” ideas that "should" have worked »
Aaron Schein · Melanie F. Pradier · Jessica Forde · Stephanie Hyland · Francisco Ruiz -
2021 Poster: Learning to Compose Visual Relations »
Nan Liu · Shuang Li · Yilun Du · Josh Tenenbaum · Antonio Torralba -
2021 Poster: Efficient Online Estimation of Causal Effects by Deciding What to Observe »
Shantanu Gupta · Zachary Lipton · David Childers -
2021 Poster: Parametric Complexity Bounds for Approximating PDEs with Neural Networks »
Tanya Marwah · Zachary Lipton · Andrej Risteski -
2021 Poster: Relative Flatness and Generalization »
Henning Petzka · Michael Kamp · Linara Adilova · Cristian Sminchisescu · Mario Boley -
2021 Poster: Learnable Fourier Features for Multi-dimensional Spatial Positional Encoding »
Yang Li · Si Si · Gang Li · Cho-Jui Hsieh · Samy Bengio -
2021 Poster: Dataset Distillation with Infinitely Wide Convolutional Networks »
Timothy Nguyen · Roman Novak · Lechao Xiao · Jaehoon Lee -
2021 Poster: Dynamic Inference with Neural Interpreters »
Nasim Rahaman · Muhammad Waleed Gondal · Shruti Joshi · Peter Gehler · Yoshua Bengio · Francesco Locatello · Bernhard Schölkopf -
2021 Poster: The future is log-Gaussian: ResNets and their infinite-depth-and-width limit at initialization »
Mufan Li · Mihai Nica · Dan Roy -
2021 Poster: Learning Signal-Agnostic Manifolds of Neural Fields »
Yilun Du · Katie Collins · Josh Tenenbaum · Vincent Sitzmann -
2021 : Traffic4cast 2021 – Temporal and Spatial Few-Shot Transfer Learning in Traffic Map Movie Forecasting + Q&A »
Moritz Neun · Christian Eichenberger · Henry Martin · Pedro Herruzo · David Jonietz · Fei Tang · Daniel Springer · Markus Spanring · Avi Avidan · Luis Ferro · Ali Soleymani · Rohit Gupta · Bo Xu · Kevin Malm · Aleksandra Gruca · Johannes Brandstetter · Michael Kopp · David Kreil · Sepp Hochreiter -
2021 Poster: Gradient Starvation: A Learning Proclivity in Neural Networks »
Mohammad Pezeshki · Oumar Kaba · Yoshua Bengio · Aaron Courville · Doina Precup · Guillaume Lajoie -
2021 Poster: Fast Multi-Resolution Transformer Fine-tuning for Extreme Multi-label Text Classification »
Jiong Zhang · Wei-Cheng Chang · Hsiang-Fu Yu · Inderjit Dhillon -
2021 Poster: Mixture Proportion Estimation and PU Learning:A Modern Approach »
Saurabh Garg · Yifan Wu · Alexander Smola · Sivaraman Balakrishnan · Zachary Lipton -
2021 Poster: Unsupervised Learning of Compositional Energy Concepts »
Yilun Du · Shuang Li · Yash Sharma · Josh Tenenbaum · Igor Mordatch -
2021 Poster: Minimax Optimal Quantile and Semi-Adversarial Regret via Root-Logarithmic Regularizers »
Jeffrey Negrea · Blair Bilodeau · Nicolò Campolongo · Francesco Orabona · Dan Roy -
2021 Poster: Deep Learning on a Data Diet: Finding Important Examples Early in Training »
Mansheej Paul · Surya Ganguli · Gintare Karolina Dziugaite -
2021 Poster: Improving Anytime Prediction with Parallel Cascaded Networks and a Temporal-Difference Loss »
Michael Iuzzolino · Michael Mozer · Samy Bengio -
2021 Poster: Hyperparameter Optimization Is Deceiving Us, and How to Stop It »
A. Feder Cooper · Yucheng Lu · Jessica Forde · Christopher De Sa -
2021 Poster: Accelerated Sparse Neural Training: A Provable and Efficient Method to Find N:M Transposable Masks »
Itay Hubara · Brian Chmiel · Moshe Island · Ron Banner · Joseph Naor · Daniel Soudry -
2021 Poster: On the Theory of Reinforcement Learning with Once-per-Episode Feedback »
Niladri Chatterji · Aldo Pacchiano · Peter Bartlett · Michael Jordan -
2021 Poster: Label Disentanglement in Partition-based Extreme Multilabel Classification »
Xuanqing Liu · Wei-Cheng Chang · Hsiang-Fu Yu · Cho-Jui Hsieh · Inderjit Dhillon -
2021 Poster: Learning curves of generic features maps for realistic datasets with a teacher-student model »
Bruno Loureiro · Cedric Gerbelot · Hugo Cui · Sebastian Goldt · Florent Krzakala · Marc Mezard · Lenka Zdeborová -
2021 Poster: The Implicit Bias of Minima Stability: A View from Function Space »
Rotem Mulayoff · Tomer Michaeli · Daniel Soudry -
2021 Poster: LLC: Accurate, Multi-purpose Learnt Low-dimensional Binary Codes »
Aditya Kusupati · Matthew Wallingford · Vivek Ramanujan · Raghav Somani · Jae Sung Park · Krishna Pillutla · Prateek Jain · Sham Kakade · Ali Farhadi -
2021 Poster: DRONE: Data-aware Low-rank Compression for Large NLP Models »
Patrick Chen · Hsiang-Fu Yu · Inderjit Dhillon · Cho-Jui Hsieh -
2021 Poster: Towards a Unified Information-Theoretic Framework for Generalization »
Mahdi Haghifam · Gintare Karolina Dziugaite · Shay Moran · Dan Roy -
2021 Poster: A Consciousness-Inspired Planning Agent for Model-Based Reinforcement Learning »
Mingde Zhao · Zhen Liu · Sitao Luan · Shuyuan Zhang · Doina Precup · Yoshua Bengio -
2021 Poster: Neural Production Systems »
Anirudh Goyal · Aniket Didolkar · Nan Rosemary Ke · Charles Blundell · Philippe Beaudoin · Nicolas Heess · Michael Mozer · Yoshua Bengio -
2021 Poster: Physics-Aware Downsampling with Deep Learning for Scalable Flood Modeling »
Niv Giladi · Zvika Ben-Haim · Sella Nevo · Yossi Matias · Daniel Soudry -
2021 Poster: Flow Network based Generative Models for Non-Iterative Diverse Candidate Generation »
Emmanuel Bengio · Moksh Jain · Maksym Korablyov · Doina Precup · Yoshua Bengio -
2021 Poster: Reverse engineering learned optimizers reveals known and novel mechanisms »
Niru Maheswaranathan · David Sussillo · Luke Metz · Ruoxi Sun · Jascha Sohl-Dickstein -
2021 : Diamond: A MineRL Competition on Training Sample-Efficient Agents + Q&A »
William Guss · Alara Dirik · Byron Galbraith · Brandon Houghton · Anssi Kanervisto · Noboru Kuno · Stephanie Milani · Sharada Mohanty · Karolis Ramanauskas · Ruslan Salakhutdinov · Rohin Shah · Nicholay Topin · Steven Wang · Cody Wild -
2021 Poster: Deep Learning Through the Lens of Example Difficulty »
Robert Baldock · Hartmut Maennel · Behnam Neyshabur -
2021 Poster: The Causal-Neural Connection: Expressiveness, Learnability, and Inference »
Kevin Xia · Kai-Zhan Lee · Yoshua Bengio · Elias Bareinboim -
2021 Poster: A Winning Hand: Compressing Deep Networks Can Improve Out-of-Distribution Robustness »
James Diffenderfer · Brian Bartoldson · Shreya Chaganti · Jize Zhang · Bhavya Kailkhura -
2021 Poster: Invariance Principle Meets Information Bottleneck for Out-of-Distribution Generalization »
Kartik Ahuja · Ethan Caballero · Dinghuai Zhang · Jean-Christophe Gagnon-Audet · Yoshua Bengio · Ioannis Mitliagkas · Irina Rish -
2021 Poster: Discrete-Valued Neural Communication »
Dianbo Liu · Alex Lamb · Kenji Kawaguchi · Anirudh Goyal · Chen Sun · Michael Mozer · Yoshua Bengio -
2021 Poster: On Component Interactions in Two-Stage Recommender Systems »
Jiri Hron · Karl Krauth · Michael Jordan · Niki Kilbertus -
2021 Poster: Off-Policy Risk Assessment in Contextual Bandits »
Audrey Huang · Liu Leqi · Zachary Lipton · Kamyar Azizzadenesheli -
2021 Poster: Rebounding Bandits for Modeling Satiation Effects »
Liu Leqi · Fatma Kilinc Karzan · Zachary Lipton · Alan Montgomery -
2021 Poster: Grounding inductive biases in natural images: invariance stems from variations in data »
Diane Bouchacourt · Mark Ibrahim · Ari Morcos -
2020 : Panel Discussion & Closing »
Yejin Choi · Alexei Efros · Chelsea Finn · Kristen Grauman · Quoc V Le · Yann LeCun · Ruslan Salakhutdinov · Eric Xing -
2020 : Spotlight Talk: Ebrahimi Kahou »
Samira Ebrahimi Kahou -
2020 : Keynote 5: Gintare Karolina Dziugaite »
Gintare Karolina Dziugaite -
2020 : Panel discussion 2 »
Danielle S Bassett · Yoshua Bengio · Cristina Savin · David Duvenaud · Anna Choromanska · Yanping Huang -
2020 : Invited Talk Yoshua Bengio »
Yoshua Bengio -
2020 : QA: Ruslan Salakhutdinov »
Ruslan Salakhutdinov -
2020 : Invited Talk: Ruslan Salakhutdinov »
Ruslan Salakhutdinov -
2020 Workshop: I Can’t Believe It’s Not Better! Bridging the gap between theory and empiricism in probabilistic machine learning »
Jessica Forde · Francisco Ruiz · Melanie Fernandez Pradier · Aaron Schein · Finale Doshi-Velez · Isabel Valera · David Blei · Hanna Wallach -
2020 : Invited Talk #7 »
Yoshua Bengio -
2020 : Pruning Neural Networks at Initialization: Why Are We Missing the Mark? »
Jonathan Frankle -
2020 : Revisiting "Qualitatively Characterizing Neural Network Optimization Problems" »
Jonathan Frankle -
2020 : Panel #1 »
Yoshua Bengio · Daniel Kahneman · Henry Kautz · Luis Lamb · Gary Marcus · Francesca Rossi -
2020 : Panel »
Kilian Weinberger · Maria De-Arteaga · Shibani Santurkar · Jonathan Frankle · Deborah Raji -
2020 : Jessica Zosa Forde - Build, Start, Run, Push: Computational Registration of ML Experiments »
Jessica Forde -
2020 : Spotlight: Machine Learning for Glacier Monitoring in the Hindu Kush Himalaya »
Kris Sankaran -
2020 : Reverse engineering learned optimizers reveals known and novel mechanisms »
Niru Maheswaranathan · David Sussillo · Luke Metz · Ruoxi Sun · Jascha Sohl-Dickstein -
2020 : Poster Session 2 (gather.town) »
Sharan Vaswani · Nicolas Loizou · Wenjie Li · Preetum Nakkiran · Zhan Gao · Sina Baghal · Jingfeng Wu · Roozbeh Yousefzadeh · Jinyi Wang · Jing Wang · Cong Xie · Anastasia Borovykh · Stanislaw Jastrzebski · Soham Dan · Yiliang Zhang · Mark Tuddenham · Sarath Pattathil · Ievgen Redko · Jeremy Cohen · Yasaman Esfandiari · Zhanhong Jiang · Mostafa ElAraby · Chulhee Yun · Michael Psenka · Robert Gower · Xiaoyu Wang -
2020 Workshop: ML Retrospectives, Surveys & Meta-Analyses (ML-RSA) »
Chhavi Yadav · Prabhu Pradhan · Jesse Dodge · Mayoore Jaiswal · Peter Henderson · Abhishek Gupta · Ryan Lowe · Jessica Forde · Joelle Pineau -
2020 : Opening Remarks »
Reinhard Heckel · Paul Hand · Soheil Feizi · Lenka Zdeborová · Richard Baraniuk -
2020 Workshop: Workshop on Deep Learning and Inverse Problems »
Reinhard Heckel · Paul Hand · Richard Baraniuk · Lenka Zdeborová · Soheil Feizi -
2020 : Yoshua Bengio - Incentives for Researchers »
Yoshua Bengio -
2020 Workshop: Machine Learning and the Physical Sciences »
Anima Anandkumar · Kyle Cranmer · Shirley Ho · Mr. Prabhat · Lenka Zdeborová · Atilim Gunes Baydin · Juan Carrasquilla · Adji Bousso Dieng · Karthik Kashinath · Gilles Louppe · Brian Nord · Michela Paganini · Savannah Thais -
2020 Workshop: Tackling Climate Change with ML »
David Dao · Evan Sherwin · Priya Donti · Lauren Kuntz · Lynn Kaack · Yumna Yusuf · David Rolnick · Catherine Nakalembe · Claire Monteleoni · Yoshua Bengio -
2020 Poster: Projection Efficient Subgradient Method and Optimal Nonsmooth Frank-Wolfe Method »
Kiran Thekumparampil · Prateek Jain · Praneeth Netrapalli · Sewoong Oh -
2020 Poster: Deep learning versus kernel learning: an empirical study of loss landscape geometry and the time evolution of the Neural Tangent Kernel »
Stanislav Fort · Gintare Karolina Dziugaite · Mansheej Paul · Sepideh Kharaghani · Daniel Roy · Surya Ganguli -
2020 Poster: Finite Versus Infinite Neural Networks: an Empirical Study »
Jaehoon Lee · Samuel Schoenholz · Jeffrey Pennington · Ben Adlam · Lechao Xiao · Roman Novak · Jascha Sohl-Dickstein -
2020 Spotlight: Finite Versus Infinite Neural Networks: an Empirical Study »
Jaehoon Lee · Samuel Schoenholz · Jeffrey Pennington · Ben Adlam · Lechao Xiao · Roman Novak · Jascha Sohl-Dickstein -
2020 Spotlight: Projection Efficient Subgradient Method and Optimal Nonsmooth Frank-Wolfe Method »
Kiran Thekumparampil · Prateek Jain · Praneeth Netrapalli · Sewoong Oh -
2020 Poster: Memory Based Trajectory-conditioned Policies for Learning from Sparse Rewards »
Yijie Guo · Jongwook Choi · Marcin Moczulski · Shengyu Feng · Samy Bengio · Mohammad Norouzi · Honglak Lee -
2020 Poster: Supervised Contrastive Learning »
Prannay Khosla · Piotr Teterwak · Chen Wang · Aaron Sarna · Yonglong Tian · Phillip Isola · Aaron Maschinot · Ce Liu · Dilip Krishnan -
2020 Poster: Untangling tradeoffs between recurrence and self-attention in artificial neural networks »
Giancarlo Kerg · Bhargav Kanuparthi · Anirudh Goyal · Kyle Goyette · Yoshua Bengio · Guillaume Lajoie -
2020 Poster: What Makes for Good Views for Contrastive Learning? »
Yonglong Tian · Chen Sun · Ben Poole · Dilip Krishnan · Cordelia Schmid · Phillip Isola -
2020 Poster: Your GAN is Secretly an Energy-based Model and You Should Use Discriminator Driven Latent Sampling »
Tong Che · Ruixiang ZHANG · Jascha Sohl-Dickstein · Hugo Larochelle · Liam Paull · Yuan Cao · Yoshua Bengio -
2020 Poster: On the training dynamics of deep networks with $L_2$ regularization »
Aitor Lewkowycz · Guy Gur-Ari -
2020 Oral: On the training dynamics of deep networks with $L_2$ regularization »
Aitor Lewkowycz · Guy Gur-Ari -
2020 Poster: LoopReg: Self-supervised Learning of Implicit Surface Correspondences, Pose and Shape for 3D Human Mesh Registration »
Bharat Lal Bhatnagar · Cristian Sminchisescu · Christian Theobalt · Gerard Pons-Moll -
2020 Poster: Robust Meta-learning for Mixed Linear Regression with Small Batches »
Weihao Kong · Raghav Somani · Sham Kakade · Sewoong Oh -
2020 Poster: JAX MD: A Framework for Differentiable Physics »
Samuel Schoenholz · Ekin Dogus Cubuk -
2020 Spotlight: JAX MD: A Framework for Differentiable Physics »
Samuel Schoenholz · Ekin Dogus Cubuk -
2020 Oral: LoopReg: Self-supervised Learning of Implicit Surface Correspondences, Pose and Shape for 3D Human Mesh Registration »
Bharat Lal Bhatnagar · Cristian Sminchisescu · Christian Theobalt · Gerard Pons-Moll -
2020 Poster: The Pitfalls of Simplicity Bias in Neural Networks »
Harshay Shah · Kaustav Tamuly · Aditi Raghunathan · Prateek Jain · Praneeth Netrapalli -
2020 Poster: Least Squares Regression with Markovian Data: Fundamental Limits and Algorithms »
Dheeraj Nagaraj · Xian Wu · Guy Bresler · Prateek Jain · Praneeth Netrapalli -
2020 Poster: Adaptive Gradient Quantization for Data-Parallel SGD »
Fartash Faghri · Iman Tabrizian · Ilia Markov · Dan Alistarh · Daniel Roy · Ali Ramezani-Kebrya -
2020 Poster: Hybrid Models for Learning to Branch »
Prateek Gupta · Maxime Gasse · Elias Khalil · Pawan K Mudigonda · Andrea Lodi · Yoshua Bengio -
2020 Poster: Modern Hopfield Networks and Attention for Immune Repertoire Classification »
Michael Widrich · Bernhard Schäfl · Milena Pavlović · Hubert Ramsauer · Lukas Gruber · Markus Holzleitner · Johannes Brandstetter · Geir Kjetil Sandve · Victor Greiff · Sepp Hochreiter · Günter Klambauer -
2020 Poster: Self-Distillation Amplifies Regularization in Hilbert Space »
Hossein Mobahi · Mehrdad Farajtabar · Peter Bartlett -
2020 Poster: Follow the Perturbed Leader: Optimism and Fast Parallel Algorithms for Smooth Minimax Games »
Arun Suggala · Praneeth Netrapalli -
2020 Poster: Implicit Bias in Deep Linear Classification: Initialization Scale vs Training Accuracy »
Edward Moroshko · Blake Woodworth · Suriya Gunasekar · Jason Lee · Nati Srebro · Daniel Soudry -
2020 Spotlight: Least Squares Regression with Markovian Data: Fundamental Limits and Algorithms »
Dheeraj Nagaraj · Xian Wu · Guy Bresler · Prateek Jain · Praneeth Netrapalli -
2020 Spotlight: Implicit Bias in Deep Linear Classification: Initialization Scale vs Training Accuracy »
Edward Moroshko · Blake Woodworth · Suriya Gunasekar · Jason Lee · Nati Srebro · Daniel Soudry -
2020 Spotlight: Modern Hopfield Networks and Attention for Immune Repertoire Classification »
Michael Widrich · Bernhard Schäfl · Milena Pavlović · Hubert Ramsauer · Lukas Gruber · Markus Holzleitner · Johannes Brandstetter · Geir Kjetil Sandve · Victor Greiff · Sepp Hochreiter · Günter Klambauer -
2020 Session: Orals & Spotlights Track 17: Kernel Methods/Optimization »
Chiranjib Bhattacharyya · Hossein Mobahi -
2020 Poster: Compositional Visual Generation with Energy Based Models »
Yilun Du · Shuang Li · Igor Mordatch -
2020 Poster: What is being transferred in transfer learning? »
Behnam Neyshabur · Hanie Sedghi · Chiyuan Zhang -
2020 Spotlight: Compositional Visual Generation with Energy Based Models »
Yilun Du · Shuang Li · Igor Mordatch -
2020 Poster: Sharpened Generalization Bounds based on Conditional Mutual Information and an Application to Noisy, Iterative Algorithms »
Mahdi Haghifam · Jeffrey Negrea · Ashish Khisti · Daniel Roy · Gintare Karolina Dziugaite -
2020 Poster: In search of robust measures of generalization »
Gintare Karolina Dziugaite · Alexandre Drouin · Brady Neal · Nitarshan Rajkumar · Ethan Caballero · Linbo Wang · Ioannis Mitliagkas · Daniel Roy -
2020 Poster: The Generalization-Stability Tradeoff In Neural Network Pruning »
Brian Bartoldson · Ari Morcos · Adrian Barbu · Gordon Erlebacher -
2020 Poster: The Lottery Ticket Hypothesis for Pre-trained BERT Networks »
Tianlong Chen · Jonathan Frankle · Shiyu Chang · Sijia Liu · Yang Zhang · Zhangyang Wang · Michael Carbin -
2020 Poster: Neural Methods for Point-wise Dependency Estimation »
Yao-Hung Hubert Tsai · Han Zhao · Makoto Yamada · Louis-Philippe Morency · Russ Salakhutdinov -
2020 Poster: MOReL: Model-Based Offline Reinforcement Learning »
Rahul Kidambi · Aravind Rajeswaran · Praneeth Netrapalli · Thorsten Joachims -
2020 Poster: Funnel-Transformer: Filtering out Sequential Redundancy for Efficient Language Processing »
Zihang Dai · Guokun Lai · Yiming Yang · Quoc V Le -
2020 Poster: Towards Learning Convolutions from Scratch »
Behnam Neyshabur -
2020 Spotlight: Neural Methods for Point-wise Dependency Estimation »
Yao-Hung Hubert Tsai · Han Zhao · Makoto Yamada · Louis-Philippe Morency · Russ Salakhutdinov -
2020 : Dr. Samy Bengio (Google Brain) »
Samy Bengio -
2019 : Panel Session: A new hope for neuroscience »
Yoshua Bengio · Blake Richards · Timothy Lillicrap · Ila Fiete · David Sussillo · Doina Precup · Konrad Kording · Surya Ganguli -
2019 : Contributed Session - Spotlight Talks »
Jonathan Frankle · David Schwab · Ari Morcos · Qianli Ma · Yao-Hung Hubert Tsai · Ruslan Salakhutdinov · YiDing Jiang · Dilip Krishnan · Hossein Mobahi · Samy Bengio · Sho Yaida · Muqiao Yang -
2019 : Panel - The Role of Communication at Large: Aparna Lakshmiratan, Jason Yosinski, Been Kim, Surya Ganguli, Finale Doshi-Velez »
Aparna Lakshmiratan · Finale Doshi-Velez · Surya Ganguli · Zachary Lipton · Michela Paganini · Anima Anandkumar · Jason Yosinski -
2019 : Afternoon Coffee Break & Poster Session »
Heidi Komkov · Stanislav Fort · Zhaoyou Wang · Rose Yu · Ji Hwan Park · Samuel Schoenholz · Taoli Cheng · Ryan-Rhys Griffiths · Chase Shimmin · Surya Karthik Mukkavili · Philippe Schwaller · Christian Knoll · Yangzesheng Sun · Keiichi Kisamori · Gavin Graham · Gavin Portwood · Hsin-Yuan Huang · Paul Novello · Moritz Munchmeyer · Anna Jungbluth · Daniel Levine · Ibrahim Ayed · Steven Atkinson · Jan Hermann · Peter Grönquist · · Priyabrata Saha · Yannik Glaser · Lingge Li · Yutaro Iiyama · Rushil Anirudh · Maciej Koch-Janusz · Vikram Sundar · Francois Lanusse · Auralee Edelen · Jonas Köhler · Jacky H. T. Yip · jiadong guo · Xiangyang Ju · Adi Hanuka · Adrian Albert · Valentina Salvatelli · Mauro Verzetti · Javier Duarte · Eric Moreno · Emmanuel de Bézenac · Athanasios Vlontzos · Alok Singh · Thomas Klijnsma · Brad Neuberg · Paul Wright · Mustafa Mustafa · David Schmidt · Steven Farrell · Hao Sun -
2019 : Poster and Coffee Break 2 »
Karol Hausman · Kefan Dong · Ken Goldberg · Lihong Li · Lin Yang · Lingxiao Wang · Lior Shani · Liwei Wang · Loren Amdahl-Culleton · Lucas Cassano · Marc Dymetman · Marc Bellemare · Marcin Tomczak · Margarita Castro · Marius Kloft · Marius-Constantin Dinu · Markus Holzleitner · Martha White · Mengdi Wang · Michael Jordan · Mihailo Jovanovic · Ming Yu · Minshuo Chen · Moonkyung Ryu · Muhammad Zaheer · Naman Agarwal · Nan Jiang · Niao He · Nikolaus Yasui · Nikos Karampatziakis · Nino Vieillard · Ofir Nachum · Olivier Pietquin · Ozan Sener · Pan Xu · Parameswaran Kamalaruban · Paul Mineiro · Paul Rolland · Philip Amortila · Pierre-Luc Bacon · Prakash Panangaden · Qi Cai · Qiang Liu · Quanquan Gu · Raihan Seraj · Richard Sutton · Rick Valenzano · Robert Dadashi · Rodrigo Toro Icarte · Roshan Shariff · Roy Fox · Ruosong Wang · Saeed Ghadimi · Samuel Sokota · Sean Sinclair · Sepp Hochreiter · Sergey Levine · Sergio Valcarcel Macua · Sham Kakade · Shangtong Zhang · Sheila McIlraith · Shie Mannor · Shimon Whiteson · Shuai Li · Shuang Qiu · Wai Lok Li · Siddhartha Banerjee · Sitao Luan · Tamer Basar · Thinh Doan · Tianhe Yu · Tianyi Liu · Tom Zahavy · Toryn Klassen · Tuo Zhao · Vicenç Gómez · Vincent Liu · Volkan Cevher · Wesley Suttle · Xiao-Wen Chang · Xiaohan Wei · Xiaotong Liu · Xingguo Li · Xinyi Chen · Xingyou Song · Yao Liu · YiDing Jiang · Yihao Feng · Yilun Du · Yinlam Chow · Yinyu Ye · Yishay Mansour · · Yonathan Efroni · Yongxin Chen · Yuanhao Wang · Bo Dai · Chen-Yu Wei · Harsh Shrivastava · Hongyang Zhang · Qinqing Zheng · SIDDHARTHA SATPATHI · Xueqing Liu · Andreu Vall -
2019 : Poster Presentations »
Rahul Mehta · Andrew Lampinen · Binghong Chen · Sergio Pascual-Diaz · Jordi Grau-Moya · Aldo Faisal · Jonathan Tompson · Yiren Lu · Khimya Khetarpal · Martin Klissarov · Pierre-Luc Bacon · Doina Precup · Thanard Kurutach · Aviv Tamar · Pieter Abbeel · Jinke He · Maximilian Igl · Shimon Whiteson · Wendelin Boehmer · Raphaël Marinier · Olivier Pietquin · Karol Hausman · Sergey Levine · Chelsea Finn · Tianhe Yu · Lisa Lee · Benjamin Eysenbach · Emilio Parisotto · Eric Xing · Ruslan Salakhutdinov · Hongyu Ren · Anima Anandkumar · Deepak Pathak · Christopher Lu · Trevor Darrell · Alexei Efros · Phillip Isola · Feng Liu · Bo Han · Gang Niu · Masashi Sugiyama · Saurabh Kumar · Janith Petangoda · Johan Ferret · James McClelland · Kara Liu · Animesh Garg · Robert Lange -
2019 : Lenka Zdeborova »
Lenka Zdeborová -
2019 : Yoshua Bengio - Towards compositional understanding of the world by agent-based deep learning »
Yoshua Bengio -
2019 : Lunch break & Poster session »
Breandan Considine · Michael Innes · Du Phan · Dougal Maclaurin · Robin Manhaeve · Alexey Radul · Shashi Gowda · Ekansh Sharma · Eli Sennesh · Maxim Kochurov · Gordon Plotkin · Thomas Wiecki · Navjot Kukreja · Chung-chieh Shan · Matthew Johnson · Dan Belov · Neeraj Pradhan · Wannes Meert · Angelika Kimmig · Luc De Raedt · Brian Patton · Matthew Hoffman · Rif A. Saurous · Daniel Roy · Eli Bingham · Martin Jankowiak · Colin Carroll · Junpeng Lao · Liam Paull · Martin Abadi · Angel Rojas Jimenez · JP Chen -
2019 : Contributed talk: What is Local Optimality in Nonconvex-Nonconcave Minimax Optimization? »
Praneeth Netrapalli -
2019 : Climate Change: A Grand Challenge for ML »
Yoshua Bengio · Carla Gomes · Andrew Ng · Jeff Dean · Lester Mackey -
2019 : Break / Poster Session 1 »
Antonia Marcu · Yao-Yuan Yang · Pascale Gourdeau · Chen Zhu · Thodoris Lykouris · Jianfeng Chi · Mark Kozdoba · Arjun Nitin Bhagoji · Xiaoxia Wu · Jay Nandy · Michael T Smith · Bingyang Wen · Yuege Xie · Konstantinos Pitas · Suprosanna Shit · Maksym Andriushchenko · Dingli Yu · Gaël Letarte · Misha Khodak · Hussein Mozannar · Chara Podimata · James Foulds · Yizhen Wang · Huishuai Zhang · Ondrej Kuzelka · Alexander Levine · Nan Lu · Zakaria Mhammedi · Paul Viallard · Diana Cai · Lovedeep Gondara · James Lucas · Yasaman Mahdaviyeh · Aristide Baratin · Rishi Bommasani · Alessandro Barp · Andrew Ilyas · Kaiwen Wu · Jens Behrmann · Omar Rivasplata · Amir Nazemi · Aditi Raghunathan · Will Stephenson · Sahil Singla · Akhil Gupta · YooJung Choi · Yannic Kilcher · Clare Lyle · Edoardo Manino · Andrew Bennett · Zhi Xu · Niladri Chatterji · Emre Barut · Flavien Prost · Rodrigo Toro Icarte · Arno Blaas · Chulhee Yun · Sahin Lale · YiDing Jiang · Tharun Kumar Reddy Medini · Ashkan Rezaei · Alexander Meinke · Stephen Mell · Gary Kazantsev · Shivam Garg · Aradhana Sinha · Vishnu Lokhande · Geovani Rizk · Han Zhao · Aditya Kumar Akash · Jikai Hou · Ali Ghodsi · Matthias Hein · Tyler Sypherd · Yichen Yang · Anastasia Pentina · Pierre Gillot · Antoine Ledent · Guy Gur-Ari · Noah MacAulay · Tianzong Zhang -
2019 : JAX, M.D.: End-to-End Differentiable, Hardware Accelerated, Molecular Dynamics in Pure Python »
Samuel Schoenholz -
2019 : Surya Ganguli, Yasaman Bahri, Florent Krzakala moderated by Lenka Zdeborova »
Florent Krzakala · Yasaman Bahri · Surya Ganguli · Lenka Zdeborová · Adji Bousso Dieng · Joan Bruna -
2019 : Florent Krzakala - Learning with "realistic" synthetic data »
Florent Krzakala -
2019 : Opening Remarks »
Manzil Zaheer · Nicholas Monath · Ari Kobren · Junier Oliva · Barnabas Poczos · Ruslan Salakhutdinov · Andrew McCallum -
2019 Workshop: Machine Learning with Guarantees »
Ben London · Gintare Karolina Dziugaite · Daniel Roy · Thorsten Joachims · Aleksander Madry · John Shawe-Taylor -
2019 Workshop: Joint Workshop on AI for Social Good »
Fei Fang · Joseph Aylett-Bullock · Marc-Antoine Dilhac · Brian Green · natalie saltiel · Dhaval Adjodah · Jack Clark · Sean McGregor · Margaux Luck · Jonathan Penn · Tristan Sylvain · Geneviève Boucher · Sydney Swaine-Simon · Girmaw Abebe Tadesse · Myriam Côté · Anna Bethke · Yoshua Bengio -
2019 Workshop: Sets and Partitions »
Nicholas Monath · Manzil Zaheer · Andrew McCallum · Ari Kobren · Junier Oliva · Barnabas Poczos · Ruslan Salakhutdinov -
2019 Workshop: Tackling Climate Change with ML »
David Rolnick · Priya Donti · Lynn Kaack · Alexandre Lacoste · Tegan Maharaj · Andrew Ng · John Platt · Jennifer Chayes · Yoshua Bengio -
2019 : Opening remarks »
Yoshua Bengio -
2019 : Poster Session »
Gergely Flamich · Shashanka Ubaru · Charles Zheng · Josip Djolonga · Kristoffer Wickstrøm · Diego Granziol · Konstantinos Pitas · Jun Li · Robert Williamson · Sangwoong Yoon · Kwot Sin Lee · Julian Zilly · Linda Petrini · Ian Fischer · Zhe Dong · Alexander Alemi · Bao-Ngoc Nguyen · Rob Brekelmans · Tailin Wu · Aditya Mahajan · Alexander Li · Kirankumar Shiragur · Yair Carmon · Linara Adilova · SHIYU LIU · Bang An · Sanjeeb Dash · Oktay Gunluk · Arya Mazumdar · Mehul Motani · Julia Rosenzweig · Michael Kamp · Marton Havasi · Leighton P Barnes · Zhengqing Zhou · Yi Hao · Dylan Foster · Yuval Benjamini · Nati Srebro · Michael Tschannen · Paul Rubenstein · Sylvain Gelly · John Duchi · Aaron Sidford · Robin Ru · Stefan Zohren · Murtaza Dalal · Michael A Osborne · Stephen J Roberts · Moses Charikar · Jayakumar Subramanian · Xiaodi Fan · Max Schwarzer · Nicholas Roberts · Simon Lacoste-Julien · Vinay Prabhu · Aram Galstyan · Greg Ver Steeg · Lalitha Sankar · Yung-Kyun Noh · Gautam Dasarathy · Frank Park · Ngai-Man (Man) Cheung · Ngoc-Trung Tran · Linxiao Yang · Ben Poole · Andrea Censi · Tristan Sylvain · R Devon Hjelm · Bangjie Liu · Jose Gallego-Posada · Tyler Sypherd · Kai Yang · Jan Nikolas Morshuis -
2019 : Poster Session »
Jonathan Scarlett · Piotr Indyk · Ali Vakilian · Adrian Weller · Partha P Mitra · Benjamin Aubin · Bruno Loureiro · Florent Krzakala · Lenka Zdeborová · Kristina Monakhova · Joshua Yurtsever · Laura Waller · Hendrik Sommerhoff · Michael Moeller · Rushil Anirudh · Shuang Qiu · Xiaohan Wei · Zhuoran Yang · Jayaraman Thiagarajan · Salman Asif · Michael Gillhofer · Johannes Brandstetter · Sepp Hochreiter · Felix Petersen · Dhruv Patel · Assad Oberai · Akshay Kamath · Sushrut Karmalkar · Eric Price · Ali Ahmed · Zahra Kadkhodaie · Sreyas Mohan · Eero Simoncelli · Carlos Fernandez-Granda · Oscar Leong · Wesam Sakla · Rebecca Willett · Stephan Hoyer · Jascha Sohl-Dickstein · Sam Greydanus · Gauri Jagatap · Chinmay Hegde · Michael Kellman · Jonathan Tamir · Nouamane Laanait · Ousmane Dia · Mirco Ravanelli · Jonathan Binas · Negar Rostamzadeh · Shirin Jalali · Tiantian Fang · Alex Schwing · Sébastien Lachapelle · Philippe Brouillard · Tristan Deleu · Simon Lacoste-Julien · Stella Yu · Arya Mazumdar · Ankit Singh Rawat · Yue Zhao · Jianshu Chen · Xiaoyang Li · Hubert Ramsauer · Gabrio Rizzuti · Nikolaos Mitsakos · Dingzhou Cao · Thomas Strohmer · Yang Li · Pei Peng · Gregory Ongie -
2019 : Coffee/Poster session 2 »
Xingyou Song · Puneet Mangla · David Salinas · Zhenxun Zhuang · Leo Feng · Shell Xu Hu · Raul Puri · Wesley Maddox · Aniruddh Raghu · Prudencio Tossou · Mingzhang Yin · Ishita Dasgupta · Kangwook Lee · Ferran Alet · Zhen Xu · Jörg Franke · James Harrison · Jonathan Warrell · Guneet Dhillon · Arber Zela · Xin Qiu · Julien Niklas Siems · Russell Mendonca · Louis Schlessinger · Jeffrey Li · Georgiana Manolache · Debojyoti Dutta · Lucas Glass · Abhishek Singh · Gregor Koehler -
2019 : Neural Reparameterization Improves Structural Optimization »
Stephan Hoyer · Jascha Sohl-Dickstein · Sam Greydanus -
2019 : Poster Session I »
Shuangjia Zheng · Arnav Kapur · Umar Asif · Eyal Rozenberg · Cyprien Gilet · Oleksii Sidorov · Yogesh Kumar · Tom Van Steenkiste · William Boag · David Ouyang · Paul Jaeger · Sheng Liu · Aparna Balagopalan · Deepta Rajan · Marta Skreta · Nikhil Pattisapu · Jann Goschenhofer · Viraj Prabhu · Di Jin · Laura-Jayne Gardiner · Irene Li · sriram kumar · Qiyuan Hu · Mehul Motani · Justin Lovelace · Usman Roshan · Lucy Lu Wang · Ilya Valmianski · Hyeonwoo Lee · Sunil Mallya · Elias Chaibub Neto · Jonas Kemp · Marie Charpignon · Amber Nigam · Wei-Hung Weng · Sabri Boughorbel · Alexis Bellot · Lovedeep Gondara · Haoran Zhang · Taha Bahadori · John Zech · Rulin Shao · Edward Choi · Laleh Seyyed-Kalantari · Emily Aiken · Ioana Bica · Yiqiu Shen · Kieran Chin-Cheong · Subhrajit Roy · Ioana Baldini · So Yeon Min · Dirk Deschrijver · Pekka Marttinen · Damian Pascual Ortiz · Supriya Nagesh · Niklas Rindtorff · Andriy Mulyar · Katharina Hoebel · Martha Shaka · Pierre Machart · Leon Gatys · Nathan Ng · Matthias Hüser · Devin Taylor · Dennis Barbour · Natalia Martinez · Clara McCreery · Benjamin Eyre · Vivek Natarajan · Ren Yi · Ruibin Ma · Chirag Nagpal · Nan Du · Chufan Gao · Anup Tuladhar · Sam Shleifer · Jason Ren · Pouria Mashouri · Ming Yang Lu · Farideh Bagherzadeh-Khiabani · Olivia Choudhury · Maithra Raghu · Scott Fleming · Mika Jain · GUO YANG · Alena Harley · Stephen Pfohl · Elisabeth Rumetshofer · Alex Fedorov · Saloni Dash · Jacob Pfau · Sabina Tomkins · Colin Targonski · Michael Brudno · Xinyu Li · Yiyang Yu · Nisarg Patel -
2019 : Approaches to Understanding AI »
Yoshua Bengio · Roel Dobbe · Madeleine Elish · Joshua Kroll · Jacob Metcalf · Jack Poulson -
2019 : The spiked matrix model with generative priors »
Lenka Zdeborová -
2019 : Invited Talk »
Yoshua Bengio -
2019 Workshop: Learning with Rich Experience: Integration of Learning Paradigms »
Zhiting Hu · Andrew Wilson · Chelsea Finn · Lisa Lee · Taylor Berg-Kirkpatrick · Ruslan Salakhutdinov · Eric Xing -
2019 Workshop: Retrospectives: A Venue for Self-Reflection in ML Research »
Ryan Lowe · Yoshua Bengio · Joelle Pineau · Michela Paganini · Jessica Forde · Shagun Sodhani · Abhishek Gupta · Joel Lehman · Peter Henderson · Kanika Madan · Koustuv Sinha · Xavier Bouthillier -
2019 Poster: XLNet: Generalized Autoregressive Pretraining for Language Understanding »
Zhilin Yang · Zihang Dai · Yiming Yang · Jaime Carbonell · Russ Salakhutdinov · Quoc V Le -
2019 Poster: Transfusion: Understanding Transfer Learning for Medical Imaging »
Maithra Raghu · Chiyuan Zhang · Jon Kleinberg · Samy Bengio -
2019 Poster: How to Initialize your Network? Robust Initialization for WeightNorm & ResNets »
Devansh Arpit · Víctor Campos · Yoshua Bengio -
2019 Poster: Information-Theoretic Generalization Bounds for SGLD via Data-Dependent Estimates »
Jeffrey Negrea · Mahdi Haghifam · Gintare Karolina Dziugaite · Ashish Khisti · Daniel Roy -
2019 Poster: Provable Non-linear Inductive Matrix Completion »
Kai Zhong · Zhao Song · Prateek Jain · Inderjit Dhillon -
2019 Poster: Efficient Algorithms for Smooth Minimax Optimization »
Kiran Thekumparampil · Prateek Jain · Praneeth Netrapalli · Sewoong Oh -
2019 Poster: Inverting Deep Generative models, One layer at a time »
Qi Lei · Ajil Jalal · Inderjit Dhillon · Alex Dimakis -
2019 Poster: Compiler Auto-Vectorization with Imitation Learning »
Charith Mendis · Cambridge Yang · Yewen Pu · Saman Amarasinghe · Michael Carbin -
2019 Poster: Wasserstein Dependency Measure for Representation Learning »
Sherjil Ozair · Corey Lynch · Yoshua Bengio · Aaron van den Oord · Sergey Levine · Pierre Sermanet -
2019 Oral: XLNet: Generalized Autoregressive Pretraining for Language Understanding »
Zhilin Yang · Zihang Dai · Yiming Yang · Jaime Carbonell · Russ Salakhutdinov · Quoc V Le -
2019 Poster: Think Globally, Act Locally: A Deep Neural Network Approach to High-Dimensional Time Series Forecasting »
Rajat Sen · Hsiang-Fu Yu · Inderjit Dhillon -
2019 Poster: AutoAssist: A Framework to Accelerate Training of Deep Neural Networks »
Jiong Zhang · Hsiang-Fu Yu · Inderjit Dhillon -
2019 Poster: A Mean Field Theory of Quantized Deep Networks: The Quantization-Depth Trade-Off »
Yaniv Blumenfeld · Dar Gilboa · Daniel Soudry -
2019 Poster: Wide Neural Networks of Any Depth Evolve as Linear Models Under Gradient Descent »
Jaehoon Lee · Lechao Xiao · Samuel Schoenholz · Yasaman Bahri · Roman Novak · Jascha Sohl-Dickstein · Jeffrey Pennington -
2019 Poster: Unsupervised State Representation Learning in Atari »
Ankesh Anand · Evan Racah · Sherjil Ozair · Yoshua Bengio · Marc-Alexandre Côté · R Devon Hjelm -
2019 Poster: Learning Neural Networks with Adaptive Regularization »
Han Zhao · Yao-Hung Hubert Tsai · Russ Salakhutdinov · Geoffrey Gordon -
2019 Poster: RUDDER: Return Decomposition for Delayed Rewards »
Jose A. Arjona-Medina · Michael Gillhofer · Michael Widrich · Thomas Unterthiner · Johannes Brandstetter · Sepp Hochreiter -
2019 Poster: Adversarial Robustness through Local Linearization »
Chongli Qin · James Martens · Sven Gowal · Dilip Krishnan · Krishnamurthy Dvijotham · Alhussein Fawzi · Soham De · Robert Stanforth · Pushmeet Kohli -
2019 Poster: The Step Decay Schedule: A Near Optimal, Geometrically Decaying Learning Rate Procedure For Least Squares »
Rong Ge · Sham Kakade · Rahul Kidambi · Praneeth Netrapalli -
2019 Poster: Dynamics of stochastic gradient descent for two-layer neural networks in the teacher-student setup »
Sebastian Goldt · Madhu Advani · Andrew Saxe · Florent Krzakala · Lenka Zdeborová -
2019 Poster: Domes to Drones: Self-Supervised Active Triangulation for 3D Human Pose Reconstruction »
Aleksis Pirinen · Erik Gärtner · Cristian Sminchisescu -
2019 Poster: Fast-rate PAC-Bayes Generalization Bounds via Shifted Rademacher Processes »
Jun Yang · Shengyang Sun · Daniel Roy -
2019 Poster: Variational Temporal Abstraction »
Taesup Kim · Sungjin Ahn · Yoshua Bengio -
2019 Poster: Gradient based sample selection for online continual learning »
Rahaf Aljundi · Min Lin · Baptiste Goujaud · Yoshua Bengio -
2019 Poster: MetaInit: Initializing learning by learning to initialize »
Yann Dauphin · Samuel Schoenholz -
2019 Poster: Primal-Dual Block Generalized Frank-Wolfe »
Qi Lei · JIACHENG ZHUO · Constantine Caramanis · Inderjit Dhillon · Alex Dimakis -
2019 Poster: MelGAN: Generative Adversarial Networks for Conditional Waveform Synthesis »
Kundan Kumar · Rithesh Kumar · Thibault de Boissiere · Lucas Gestin · Wei Zhen Teoh · Jose Sotelo · Alexandre de Brébisson · Yoshua Bengio · Aaron Courville -
2019 Oral: Dynamics of stochastic gradient descent for two-layer neural networks in the teacher-student setup »
Sebastian Goldt · Madhu Advani · Andrew Saxe · Florent Krzakala · Lenka Zdeborová -
2019 Invited Talk: From System 1 Deep Learning to System 2 Deep Learning »
Yoshua Bengio -
2019 Poster: Post training 4-bit quantization of convolutional networks for rapid-deployment »
Ron Banner · Yury Nahshan · Daniel Soudry -
2019 Poster: Language as an Abstraction for Hierarchical Deep Reinforcement Learning »
YiDing Jiang · Shixiang (Shane) Gu · Kevin Murphy · Chelsea Finn -
2019 Poster: On Adversarial Mixup Resynthesis »
Christopher Beckham · Sina Honari · Alex Lamb · Vikas Verma · Farnoosh Ghadiri · R Devon Hjelm · Yoshua Bengio · Chris Pal -
2019 Poster: Implicit Generation and Modeling with Energy Based Models »
Yilun Du · Igor Mordatch -
2019 Poster: Invertible Convolutional Flow »
Mahdi Karami · Dale Schuurmans · Jascha Sohl-Dickstein · Laurent Dinh · Daniel Duckworth -
2019 Poster: Who is Afraid of Big Bad Minima? Analysis of gradient-flow in spiked matrix-tensor models »
Stefano Sarao Mannelli · Giulio Biroli · Chiara Cammarota · Florent Krzakala · Lenka Zdeborová -
2019 Spotlight: Who is Afraid of Big Bad Minima? Analysis of gradient-flow in spiked matrix-tensor models »
Stefano Sarao Mannelli · Giulio Biroli · Chiara Cammarota · Florent Krzakala · Lenka Zdeborová -
2019 Spotlight: Invertible Convolutional Flow »
Mahdi Karami · Dale Schuurmans · Jascha Sohl-Dickstein · Laurent Dinh · Daniel Duckworth -
2019 Spotlight: Implicit Generation and Modeling with Energy Based Models »
Yilun Du · Igor Mordatch -
2019 Poster: Updates of Equilibrium Prop Match Gradients of Backprop Through Time in an RNN with Static Input »
Maxence Ernoult · Julie Grollier · Damien Querlioz · Yoshua Bengio · Benjamin Scellier -
2019 Poster: Successor Uncertainties: Exploration and Uncertainty in Temporal Difference Learning »
David Janz · Jiri Hron · Przemysław Mazur · Katja Hofmann · José Miguel Hernández-Lobato · Sebastian Tschiatschek -
2019 Poster: One ticket to win them all: generalizing lottery ticket initializations across datasets and optimizers »
Ari Morcos · Haonan Yu · Michela Paganini · Yuandong Tian -
2019 Poster: Re-examination of the Role of Latent Variables in Sequence Modeling »
Guokun Lai · Zihang Dai · Yiming Yang · Shinjae Yoo -
2019 Poster: Non-normal Recurrent Neural Network (nnRNN): learning long time dependencies while improving expressivity with transient dynamics »
Giancarlo Kerg · Kyle Goyette · Maximilian Puelma Touzel · Gauthier Gidel · Eugene Vorontsov · Yoshua Bengio · Guillaume Lajoie -
2019 Oral: Updates of Equilibrium Prop Match Gradients of Backprop Through Time in an RNN with Static Input »
Maxence Ernoult · Julie Grollier · Damien Querlioz · Yoshua Bengio · Benjamin Scellier -
2018 : Panel Discussion »
Rich Caruana · Mike Schuster · Ralf Schlüter · Hynek Hermansky · Renato De Mori · Samy Bengio · Michiel Bacchiani · Jason Eisner -
2018 : Poster Session »
Sujay Sanghavi · Vatsal Shah · Yanyao Shen · Tianchen Zhao · Yuandong Tian · Tomer Galanti · Mufan Li · Gilad Cohen · Daniel Rothchild · Aristide Baratin · Devansh Arpit · Vagelis Papalexakis · Michael Perlmutter · Ashok Vardhan Makkuva · Pim de Haan · Yingyan Lin · Wanmo Kang · Cheolhyoung Lee · Hao Shen · Sho Yaida · Dan Roberts · Nadav Cohen · Philippe Casgrain · Dejiao Zhang · Tengyu Ma · Avinash Ravichandran · Julian Emilio Salazar · Bo Li · Davis Liang · Christopher Wong · Glen Bigan Mbeng · Animesh Garg -
2018 : Opening remarks »
Yoshua Bengio -
2018 Workshop: AI for social good »
Margaux Luck · Tristan Sylvain · Joseph Paul Cohen · Arsene Fansi Tchango · Valentine Goddard · Aurelie Helouis · Yoshua Bengio · Sam Greydanus · Cody Wild · Taras Kucherenko · Arya Farahi · Jonathan Penn · Sean McGregor · Mark Crowley · Abhishek Gupta · Kenny Chen · Myriam Côté · Rediet Abebe -
2018 : Poster spotlight session. »
Abdullah Salama · Wei-Cheng Chang · Aidan Gomez · Raphael Tang · FUXUN YU · Zhendong Zhang · Yuxin Zhang · Ji Lin · Stephen Tiedemann · Kun Bai · Sivaramakrishnan Sankarapandian · Marton Havasi · Jack Turner · Hsin-Pai Cheng · Yue Wang · Xiaofan Xu · Ruizhou Ding · Haoji Hu · Mohammad Shafiee · Christopher Blake · Chieh-Chi Kao · Daniel Kang · Yew Ken Chia · Amir Ashouri · Sourya Basu · Simon Wiedemann · Thorsten Laude -
2018 : Poster Session 1 (note there are numerous missing names here, all papers appear in all poster sessions) »
Akhilesh Gotmare · Kenneth Holstein · Jan Brabec · Michal Uricar · Kaleigh Clary · Cynthia Rudin · Sam Witty · Andrew Ross · Shayne O'Brien · Babak Esmaeili · Jessica Forde · Massimo Caccia · Ali Emami · Scott Jordan · Bronwyn Woods · D. Sculley · Rebekah Overdorf · Nicolas Le Roux · Peter Henderson · Brandon Yang · Tzu-Yu Liu · David Jensen · Niccolo Dalmasso · Weitang Liu · Paul Marc TRICHELAIR · Jun Ki Lee · Akanksha Atrey · Matt Groh · Yotam Hechtlinger · Emma Tosch -
2018 : Poster Session 1 »
Stefan Gadatsch · Danil Kuzin · Navneet Kumar · Patrick Dallaire · Tom Ryder · Remus-Petru Pop · Nathan Hunt · Adam Kortylewski · Sophie Burkhardt · Mahmoud Elnaggar · Dieterich Lawson · Yifeng Li · Jongha (Jon) Ryu · Juhan Bae · Micha Livne · Tim Pearce · Mariia Vladimirova · Jason Ramapuram · Jiaming Zeng · Xinyu Hu · Jiawei He · Danielle Maddix · Arunesh Mittal · Albert Shaw · Tuan Anh Le · Alexander Sagel · Lisha Chen · Victor Gallego · Mahdi Karami · Zihao Zhang · Tal Kachman · Noah Weber · Matt Benatan · Kumar K Sricharan · Vincent Cartillier · Ivan Ovinnikov · Buu Phan · Mahmoud Hossam · Liu Ziyin · Valerii Kharitonov · Eugene Golikov · Qiang Zhang · Jae Myung Kim · Sebastian Farquhar · Jishnu Mukhoti · Xu Hu · Gregory Gundersen · Lavanya Sita Tekumalla · Paris Perdikaris · Ershad Banijamali · Siddhartha Jain · Ge Liu · Martin Gottwald · Katy Blumer · Sukmin Yun · Ranganath Krishnan · Roman Novak · Yilun Du · Yu Gong · Beliz Gokkaya · Jessica Ai · Daniel Duckworth · Johannes von Oswald · Christian Henning · Louis-Philippe Morency · Ali Ghodsi · Mahesh Subedar · Jean-Pascal Pfister · Rémi Lebret · Chao Ma · Aleksander Wieczorek · Laurence Perreault Levasseur -
2018 : Spotlight talks (session 1) »
Denisa Roberts · David Kozak · Kehinde Owoeye · astrid dahl · Abdi-Hakin Dirie · Wei-Cheng Chang · Vladimir Ivashkin -
2018 Poster: Norm matters: efficient and accurate normalization schemes in deep networks »
Elad Hoffer · Ron Banner · Itay Golan · Daniel Soudry -
2018 Poster: Support Recovery for Orthogonal Matching Pursuit: Upper and Lower bounds »
Raghav Somani · Chirag Gupta · Prateek Jain · Praneeth Netrapalli -
2018 Spotlight: Support Recovery for Orthogonal Matching Pursuit: Upper and Lower bounds »
Raghav Somani · Chirag Gupta · Prateek Jain · Praneeth Netrapalli -
2018 Spotlight: Norm matters: efficient and accurate normalization schemes in deep networks »
Elad Hoffer · Ron Banner · Itay Golan · Daniel Soudry -
2018 Poster: Large Margin Deep Networks for Classification »
Gamaleldin Elsayed · Dilip Krishnan · Hossein Mobahi · Kevin Regan · Samy Bengio -
2018 Poster: Image-to-image translation for cross-domain disentanglement »
Abel Gonzalez-Garcia · Joost van de Weijer · Yoshua Bengio -
2018 Poster: Entropy and mutual information in models of deep neural networks »
Marylou Gabrié · Andre Manoel · Clément Luneau · jean barbier · Nicolas Macris · Florent Krzakala · Lenka Zdeborová -
2018 Poster: The committee machine: Computational to statistical gaps in learning a two-layers neural network »
Benjamin Aubin · Antoine Maillard · jean barbier · Florent Krzakala · Nicolas Macris · Lenka Zdeborová -
2018 Poster: Implicit Bias of Gradient Descent on Linear Convolutional Networks »
Suriya Gunasekar · Jason Lee · Daniel Soudry · Nati Srebro -
2018 Poster: Towards Deep Conversational Recommendations »
Raymond Li · Samira Ebrahimi Kahou · Hannes Schulz · Vincent Michalski · Laurent Charlin · Chris Pal -
2018 Spotlight: The committee machine: Computational to statistical gaps in learning a two-layers neural network »
Benjamin Aubin · Antoine Maillard · jean barbier · Florent Krzakala · Nicolas Macris · Lenka Zdeborová -
2018 Spotlight: Entropy and mutual information in models of deep neural networks »
Marylou Gabrié · Andre Manoel · Clément Luneau · jean barbier · Nicolas Macris · Florent Krzakala · Lenka Zdeborová -
2018 Poster: Learning to Share and Hide Intentions using Information Regularization »
DJ Strouse · Max Kleiman-Weiner · Josh Tenenbaum · Matt Botvinick · David Schwab -
2018 Poster: Learning to Exploit Stability for 3D Scene Parsing »
Yilun Du · Zhijian Liu · Hector Basevi · Ales Leonardis · Bill Freeman · Josh Tenenbaum · Jiajun Wu -
2018 Poster: MetaGAN: An Adversarial Approach to Few-Shot Learning »
Ruixiang ZHANG · Tong Che · Zoubin Ghahramani · Yoshua Bengio · Yangqiu Song -
2018 Poster: Insights on representational similarity in neural networks with canonical correlation »
Ari Morcos · Maithra Raghu · Samy Bengio -
2018 Poster: Deep Network for the Integrated 3D Sensing of Multiple People in Natural Images »
Andrei Zanfir · Elisabeta Marinoiu · Mihai Zanfir · Alin-Ionut Popa · Cristian Sminchisescu -
2018 Poster: Data-dependent PAC-Bayes priors via differential privacy »
Gintare Karolina Dziugaite · Daniel Roy -
2018 Poster: PCA of high dimensional random walks with comparison to neural network training »
Joseph Antognini · Jascha Sohl-Dickstein -
2018 Poster: MixLasso: Generalized Mixed Regression via Convex Atomic-Norm Regularization »
Ian En-Hsu Yen · Wei-Cheng Lee · Kai Zhong · Sung-En Chang · Pradeep Ravikumar · Shou-De Lin -
2018 Spotlight: Deep Network for the Integrated 3D Sensing of Multiple People in Natural Images »
Andrei Zanfir · Elisabeta Marinoiu · Mihai Zanfir · Alin-Ionut Popa · Cristian Sminchisescu -
2018 Poster: Neural Code Comprehension: A Learnable Representation of Code Semantics »
Tal Ben-Nun · Alice Shoshana Jakobovits · Torsten Hoefler -
2018 Poster: Bayesian Model-Agnostic Meta-Learning »
Jaesik Yoon · Taesup Kim · Ousmane Dia · Sungwoong Kim · Yoshua Bengio · Sungjin Ahn -
2018 Poster: Sparse Attentive Backtracking: Temporal Credit Assignment Through Reminding »
Nan Rosemary Ke · Anirudh Goyal · Olexa Bilaniuk · Jonathan Binas · Michael Mozer · Chris Pal · Yoshua Bengio -
2018 Spotlight: Sparse Attentive Backtracking: Temporal Credit Assignment Through Reminding »
Nan Rosemary Ke · Anirudh Goyal · Olexa Bilaniuk · Jonathan Binas · Michael Mozer · Chris Pal · Yoshua Bengio -
2018 Spotlight: Bayesian Model-Agnostic Meta-Learning »
Jaesik Yoon · Taesup Kim · Ousmane Dia · Sungwoong Kim · Yoshua Bengio · Sungjin Ahn -
2018 Poster: Adversarial Examples that Fool both Computer Vision and Time-Limited Humans »
Gamaleldin Elsayed · Shreya Shankar · Brian Cheung · Nicolas Papernot · Alexey Kurakin · Ian Goodfellow · Jascha Sohl-Dickstein -
2018 Poster: Content preserving text generation with attribute controls »
Lajanugen Logeswaran · Honglak Lee · Samy Bengio -
2018 Poster: Scalable methods for 8-bit training of neural networks »
Ron Banner · Itay Hubara · Elad Hoffer · Daniel Soudry -
2018 Poster: Dendritic cortical microcircuits approximate the backpropagation algorithm »
João Sacramento · Rui Ponte Costa · Yoshua Bengio · Walter Senn -
2018 Demonstration: Reproducing Machine Learning Research on Binder »
Jessica Forde · Tim Head · Chris Holdgraf · M Pacer · Félix-Antoine Fortin · Fernando Perez -
2018 Oral: Dendritic cortical microcircuits approximate the backpropagation algorithm »
João Sacramento · Rui Ponte Costa · Yoshua Bengio · Walter Senn -
2017 : Daniel Roy - Deep Neural Networks: From Flat Minima to Numerically Nonvacuous Generalization Bounds via PAC-Bayes »
Daniel Roy -
2017 : Yoshua Bengio »
Yoshua Bengio -
2017 : From deep learning of disentangled representations to higher-level cognition »
Yoshua Bengio -
2017 : Deep Kernel Learning »
Ruslan Salakhutdinov -
2017 : Contributed talk 1 - A PAC-Bayesian Approach to Spectrally-Normalized Margin Bounds for Neural Networks »
Behnam Neyshabur -
2017 : More Steps towards Biologically Plausible Backprop »
Yoshua Bengio -
2017 : Closing the Generalization Gap »
Itay Hubara -
2017 : Coffee break and Poster Session II »
Mohamed Kane · Albert Haque · Vagelis Papalexakis · John Guibas · Peter Li · Carlos Arias · Eric Nalisnick · Padhraic Smyth · Frank Rudzicz · Xia Zhu · Theodore Willke · Noemie Elhadad · Hans Raffauf · Harini Suresh · Paroma Varma · Yisong Yue · Ognjen (Oggi) Rudovic · Luca Foschini · Syed Rameel Ahmad · Hasham ul Haq · Valerio Maggio · Giuseppe Jurman · Sonali Parbhoo · Pouya Bashivan · Jyoti Islam · Mirco Musolesi · Chris Wu · Alexander Ratner · Jared Dunnmon · Cristóbal Esteban · Aram Galstyan · Greg Ver Steeg · Hrant Khachatrian · Marc Górriz · Mihaela van der Schaar · Anton Nemchenko · Manasi Patwardhan · Tanay Tandon -
2017 : A3T: Adversarially Augmented Adversarial Training »
Aristide Baratin · Simon Lacoste-Julien · Yoshua Bengio · Akram Erraqabi -
2017 : Competition III: The Conversational Intelligence Challenge »
Mikhail Burtsev · Ryan Lowe · Iulian Vlad Serban · Yoshua Bengio · Alexander Rudnicky · Alan W Black · Shrimai Prabhumoye · Artem Rodichev · Nikita Smetanin · Denis Fedorenko · CheongAn Lee · EUNMI HONG · Hwaran Lee · Geonmin Kim · Nicolas Gontier · Atsushi Saito · Andrey Gershfeld · Artem Burachenok -
2017 : Coffee break and Poster Session I »
Nishith Khandwala · Steve Gallant · Gregory Way · Aniruddh Raghu · Li Shen · Aydan Gasimova · Alican Bozkurt · William Boag · Daniel Lopez-Martinez · Ulrich Bodenhofer · Samaneh Nasiri GhoshehBolagh · Michelle Guo · Christoph Kurz · Kirubin Pillay · Kimis Perros · George H Chen · Alexandre Yahi · Madhumita Sushil · Sanjay Purushotham · Elena Tutubalina · Tejpal Virdi · Marc-Andre Schulz · Samuel Weisenthal · Bharat Srikishan · Petar Veličković · Kartik Ahuja · Andrew Miller · Erin Craig · Disi Ji · Filip Dabek · Chloé Pou-Prom · Hejia Zhang · Janani Kalyanam · Wei-Hung Weng · Harish Bhat · Hugh Chen · Simon Kohl · Mingwu Gao · Tingting Zhu · Ming-Zher Poh · Iñigo Urteaga · Antoine Honoré · Alessandro De Palma · Maruan Al-Shedivat · Pranav Rajpurkar · Matthew McDermott · Vincent Chen · Yanan Sui · Yun-Geun Lee · Li-Fang Cheng · Chen Fang · Sibt ul Hussain · Cesare Furlanello · Zeev Waks · Hiba Chougrad · Hedvig Kjellstrom · Finale Doshi-Velez · Wolfgang Fruehwirt · Yanqing Zhang · Lily Hu · Junfang Chen · Sunho Park · Gatis Mikelsons · Jumana Dakka · Stephanie Hyland · yann chevaleyre · Hyunwoo Lee · Xavier Giro-i-Nieto · David Kale · Michael Hughes · Gabriel Erion · Rishab Mehra · William Zame · Stojan Trajanovski · Prithwish Chakraborty · Kelly Peterson · Muktabh Mayank Srivastava · Amy Jin · Heliodoro Tejeda Lemus · Priyadip Ray · Tamas Madl · Joseph Futoma · Enhao Gong · Syed Rameel Ahmad · Eric Lei · Ferdinand Legros -
2017 : Graph based Feature Selection for Structured High Dimensional Data (poster). »
Yanqing Zhang -
2017 : Competition I: Adversarial Attacks and Defenses »
Alexey Kurakin · Ian Goodfellow · Samy Bengio · Yao Zhao · Yinpeng Dong · Tianyu Pang · Fangzhou Liao · Cihang Xie · Adithya Ganesh · Oguz Elibol -
2017 Oral: Deep Sets »
Manzil Zaheer · Satwik Kottur · Siamak Ravanbakhsh · Barnabas Poczos · Ruslan Salakhutdinov · Alexander Smola -
2017 Poster: Train longer, generalize better: closing the generalization gap in large batch training of neural networks »
Elad Hoffer · Itay Hubara · Daniel Soudry -
2017 Poster: MMD GAN: Towards Deeper Understanding of Moment Matching Network »
Chun-Liang Li · Wei-Cheng Chang · Yu Cheng · Yiming Yang · Barnabas Poczos -
2017 Poster: REBAR: Low-variance, unbiased gradient estimates for discrete latent variable models »
George Tucker · Andriy Mnih · Chris J Maddison · John Lawson · Jascha Sohl-Dickstein -
2017 Poster: Deep Sets »
Manzil Zaheer · Satwik Kottur · Siamak Ravanbakhsh · Barnabas Poczos · Ruslan Salakhutdinov · Alexander Smola -
2017 Poster: Concrete Dropout »
Yarin Gal · Jiri Hron · Alex Kendall -
2017 Poster: Variational Walkback: Learning a Transition Operator as a Stochastic Recurrent Net »
Anirudh Goyal · Nan Rosemary Ke · Surya Ganguli · Yoshua Bengio -
2017 Poster: A Greedy Approach for Budgeted Maximum Inner Product Search »
Hsiang-Fu Yu · Cho-Jui Hsieh · Qi Lei · Inderjit Dhillon -
2017 Poster: Good Semi-supervised Learning That Requires a Bad GAN »
Zihang Dai · Zhilin Yang · Fan Yang · William Cohen · Ruslan Salakhutdinov -
2017 Oral: REBAR: Low-variance, unbiased gradient estimates for discrete latent variable models »
George Tucker · Andriy Mnih · Chris J Maddison · John Lawson · Jascha Sohl-Dickstein -
2017 Oral: Train longer, generalize better: closing the generalization gap in large batch training of neural networks »
Elad Hoffer · Itay Hubara · Daniel Soudry -
2017 Demonstration: A Deep Reinforcement Learning Chatbot »
Iulian Vlad Serban · Chinnadhurai Sankar · Mathieu Germain · Saizheng Zhang · Zhouhan Lin · Sandeep Subramanian · Taesup Kim · Michael Pieper · Sarath Chandar · Nan Rosemary Ke · Sai Rajeswar Mudumba · Alexandre de Brébisson · Jose Sotelo · Dendi A Suhubdy · Vincent Michalski · Joelle Pineau · Yoshua Bengio -
2017 Poster: Alternating minimization for dictionary learning with random initialization »
Niladri Chatterji · Peter Bartlett -
2017 Poster: GibbsNet: Iterative Adversarial Inference for Deep Graphical Models »
Alex Lamb · R Devon Hjelm · Yaroslav Ganin · Joseph Paul Cohen · Aaron Courville · Yoshua Bengio -
2017 Poster: Exploring Generalization in Deep Learning »
Behnam Neyshabur · Srinadh Bhojanapalli · David Mcallester · Nati Srebro -
2017 Poster: Implicit Regularization in Matrix Factorization »
Suriya Gunasekar · Blake Woodworth · Srinadh Bhojanapalli · Behnam Neyshabur · Nati Srebro -
2017 Spotlight: Implicit Regularization in Matrix Factorization »
Suriya Gunasekar · Blake Woodworth · Srinadh Bhojanapalli · Behnam Neyshabur · Nati Srebro -
2017 Poster: Mean Field Residual Networks: On the Edge of Chaos »
Ge Yang · Samuel Schoenholz -
2017 Poster: Resurrecting the sigmoid in deep learning through dynamical isometry: theory and practice »
Jeffrey Pennington · Samuel Schoenholz · Surya Ganguli -
2017 Poster: Plan, Attend, Generate: Planning for Sequence-to-Sequence Models »
Caglar Gulcehre · Francis Dutil · Adam Trischler · Yoshua Bengio -
2017 Poster: SVCCA: Singular Vector Canonical Correlation Analysis for Deep Learning Dynamics and Interpretability »
Maithra Raghu · Justin Gilmer · Jason Yosinski · Jascha Sohl-Dickstein -
2017 Poster: Z-Forcing: Training Stochastic Recurrent Networks »
Anirudh Goyal · Alessandro Sordoni · Marc-Alexandre Côté · Nan Rosemary Ke · Yoshua Bengio -
2017 Poster: Active Learning from Peers »
Keerthiram Murugesan · Jaime Carbonell -
2016 : Yoshua Bengio – Credit assignment: beyond backpropagation »
Yoshua Bengio -
2016 : From Brains to Bits and Back Again »
Yoshua Bengio · Terrence Sejnowski · Christos H Papadimitriou · Jakob H Macke · Demis Hassabis · Alyson Fletcher · Andreas Tolias · Jascha Sohl-Dickstein · Konrad P Koerding -
2016 : Yoshua Bengio : Toward Biologically Plausible Deep Learning »
Yoshua Bengio -
2016 : Opening Remarks »
Jascha Sohl-Dickstein -
2016 : Panel on "Explainable AI" (Yoshua Bengio, Alessio Lomuscio, Gary Marcus, Stephen Muggleton, Michael Witbrock) »
Yoshua Bengio · Alessio Lomuscio · Gary Marcus · Stephen H Muggleton · Michael Witbrock -
2016 : Yoshua Bengio: From Training Low Precision Neural Nets to Training Analog Continuous-Time Machines »
Yoshua Bengio -
2016 Workshop: Extreme Classification: Multi-class and Multi-label Learning in Extremely Large Label Spaces »
Moustapha Cisse · Manik Varma · Samy Bengio -
2016 Workshop: Learning in High Dimensions with Structure »
Nikhil Rao · Prateek Jain · Hsiang-Fu Yu · Ming Yuan · Francis Bach -
2016 Workshop: Brains and Bits: Neuroscience meets Machine Learning »
Alyson Fletcher · Eva Dyer · Jascha Sohl-Dickstein · Joshua T Vogelstein · Konrad Koerding · Jakob H Macke -
2016 Symposium: Deep Learning Symposium »
Yoshua Bengio · Yann LeCun · Navdeep Jaitly · Roger Grosse -
2016 Poster: Asynchronous Parallel Greedy Coordinate Descent »
Yang You · Xiangru Lian · Ji Liu · Hsiang-Fu Yu · Inderjit Dhillon · James Demmel · Cho-Jui Hsieh -
2016 Poster: Architectural Complexity Measures of Recurrent Neural Networks »
Saizheng Zhang · Yuhuai Wu · Tong Che · Zhouhan Lin · Roland Memisevic · Russ Salakhutdinov · Yoshua Bengio -
2016 Poster: Professor Forcing: A New Algorithm for Training Recurrent Networks »
Alex M Lamb · Anirudh Goyal · Ying Zhang · Saizheng Zhang · Aaron Courville · Yoshua Bengio -
2016 Poster: Coordinate-wise Power Method »
Qi Lei · Kai Zhong · Inderjit Dhillon -
2016 Poster: Structured Sparse Regression via Greedy Hard Thresholding »
Prateek Jain · Nikhil Rao · Inderjit Dhillon -
2016 Poster: Measuring the reliability of MCMC inference with bidirectional Monte Carlo »
Roger Grosse · Siddharth Ancha · Daniel Roy -
2016 Poster: Can Active Memory Replace Attention? »
Łukasz Kaiser · Samy Bengio -
2016 Poster: An Online Sequence-to-Sequence Model Using Partial Conditioning »
Navdeep Jaitly · Quoc V Le · Oriol Vinyals · Ilya Sutskever · David Sussillo · Samy Bengio -
2016 Poster: Exponential expressivity in deep neural networks through transient chaos »
Ben Poole · Subhaneil Lahiri · Maithra Raghu · Jascha Sohl-Dickstein · Surya Ganguli -
2016 Poster: On Multiplicative Integration with Recurrent Neural Networks »
Yuhuai Wu · Saizheng Zhang · Ying Zhang · Yoshua Bengio · Russ Salakhutdinov -
2016 Poster: Mixed Linear Regression with Multiple Components »
Kai Zhong · Prateek Jain · Inderjit Dhillon -
2016 Poster: Domain Separation Networks »
Konstantinos Bousmalis · George Trigeorgis · Nathan Silberman · Dilip Krishnan · Dumitru Erhan -
2016 Poster: Reward Augmented Maximum Likelihood for Neural Structured Prediction »
Mohammad Norouzi · Samy Bengio · zhifeng Chen · Navdeep Jaitly · Mike Schuster · Yonghui Wu · Dale Schuurmans -
2016 Poster: Binarized Neural Networks »
Itay Hubara · Matthieu Courbariaux · Daniel Soudry · Ran El-Yaniv · Yoshua Bengio -
2016 Poster: Temporal Regularized Matrix Factorization for High-dimensional Time Series Prediction »
Hsiang-Fu Yu · Nikhil Rao · Inderjit Dhillon -
2016 Poster: Adaptive Smoothed Online Multi-Task Learning »
Keerthiram Murugesan · Hanxiao Liu · Jaime Carbonell · Yiming Yang -
2016 Poster: Dual Decomposed Learning with Factorwise Oracle for Structural SVM of Large Output Domain »
Ian En-Hsu Yen · Xiangru Huang · Kai Zhong · Ruohan Zhang · Pradeep Ravikumar · Inderjit Dhillon -
2015 Workshop: Multiresolution methods for large-scale learning »
Inderjit Dhillon · Risi Kondor · Rob Nowak · Michael O'Neil · Nedelina Teneva -
2015 : Temporal Regularized Matrix Factorization »
Hsiang-Fu Yu -
2015 : RL for DL »
Yoshua Bengio -
2015 : Learning Representations for Unsupervised and Transfer Learning »
Yoshua Bengio -
2015 : Spotlight Part II »
Alex Gibberd · Kenji Doya · Bhaswar B Bhattacharya · Sakyasingha Dasgupta · Daniel Soudry -
2015 Workshop: Statistical Methods for Understanding Neural Systems »
Alyson Fletcher · Jakob H Macke · Ryan Adams · Jascha Sohl-Dickstein -
2015 Symposium: Deep Learning Symposium »
Yoshua Bengio · Marc'Aurelio Ranzato · Honglak Lee · Max Welling · Andrew Y Ng -
2015 Poster: Scheduled Sampling for Sequence Prediction with Recurrent Neural Networks »
Samy Bengio · Oriol Vinyals · Navdeep Jaitly · Noam Shazeer -
2015 Poster: Matrix Completion with Noisy Side Information »
Kai-Yang Chiang · Cho-Jui Hsieh · Inderjit Dhillon -
2015 Poster: Collaborative Filtering with Graph Information: Consistency and Scalable Methods »
Nikhil Rao · Hsiang-Fu Yu · Pradeep Ravikumar · Inderjit Dhillon -
2015 Spotlight: Collaborative Filtering with Graph Information: Consistency and Scalable Methods »
Nikhil Rao · Hsiang-Fu Yu · Pradeep Ravikumar · Inderjit Dhillon -
2015 Spotlight: Matrix Completion with Noisy Side Information »
Kai-Yang Chiang · Cho-Jui Hsieh · Inderjit Dhillon -
2015 Poster: Sparse Linear Programming via Primal and Dual Augmented Coordinate Descent »
Ian En-Hsu Yen · Kai Zhong · Cho-Jui Hsieh · Pradeep Ravikumar · Inderjit Dhillon -
2015 Poster: Fixed-Length Poisson MRF: Adding Dependencies to the Multinomial »
David I Inouye · Pradeep Ravikumar · Inderjit Dhillon -
2015 Poster: Consistent Multilabel Classification »
Oluwasanmi Koyejo · Nagarajan Natarajan · Pradeep Ravikumar · Inderjit Dhillon -
2015 Poster: Attention-Based Models for Speech Recognition »
Jan K Chorowski · Dzmitry Bahdanau · Dmitriy Serdyuk · Kyunghyun Cho · Yoshua Bengio -
2015 Poster: Equilibrated adaptive learning rates for non-convex optimization »
Yann Dauphin · Harm de Vries · Yoshua Bengio -
2015 Spotlight: Equilibrated adaptive learning rates for non-convex optimization »
Yann Dauphin · Harm de Vries · Yoshua Bengio -
2015 Spotlight: Attention-Based Models for Speech Recognition »
Jan K Chorowski · Dzmitry Bahdanau · Dmitriy Serdyuk · Kyunghyun Cho · Yoshua Bengio -
2015 Poster: Deep Knowledge Tracing »
Chris Piech · Jonathan Bassen · Jonathan Huang · Surya Ganguli · Mehran Sahami · Leonidas Guibas · Jascha Sohl-Dickstein -
2015 Poster: Matrix Completion from Fewer Entries: Spectral Detectability and Rank Estimation »
Alaa Saade · Florent Krzakala · Lenka Zdeborová -
2015 Poster: A Recurrent Latent Variable Model for Sequential Data »
Junyoung Chung · Kyle Kastner · Laurent Dinh · Kratarth Goel · Aaron Courville · Yoshua Bengio -
2015 Poster: BinaryConnect: Training Deep Neural Networks with binary weights during propagations »
Matthieu Courbariaux · Yoshua Bengio · Jean-Pierre David -
2015 Tutorial: Deep Learning »
Geoffrey E Hinton · Yoshua Bengio · Yann LeCun -
2014 Workshop: Second Workshop on Transfer and Multi-Task Learning: Theory meets Practice »
Urun Dogan · Tatiana Tommasi · Yoshua Bengio · Francesco Orabona · Marius Kloft · Andres Munoz · Gunnar Rätsch · Hal Daumé III · Mehryar Mohri · Xuezhi Wang · Daniel Hernández-lobato · Song Liu · Thomas Unterthiner · Pascal Germain · Vinay P Namboodiri · Michael Goetz · Christopher Berlind · Sigurd Spieckermann · Marta Soare · Yujia Li · Vitaly Kuznetsov · Wenzhao Lian · Daniele Calandriello · Emilie Morvant -
2014 Workshop: 3rd NIPS Workshop on Probabilistic Programming »
Daniel Roy · Josh Tenenbaum · Thomas Dietterich · Stuart J Russell · YI WU · Ulrik R Beierholm · Alp Kucukelbir · Zenna Tavares · Yura Perov · Daniel Lee · Brian Ruttenberg · Sameer Singh · Michael Hughes · Marco Gaboardi · Alexey Radul · Vikash Mansinghka · Frank Wood · Sebastian Riedel · Prakash Panangaden -
2014 Workshop: Deep Learning and Representation Learning »
Andrew Y Ng · Yoshua Bengio · Adam Coates · Roland Memisevic · Sharanyan Chetlur · Geoffrey E Hinton · Shamim Nemati · Bryan Catanzaro · Surya Ganguli · Herbert Jaeger · Phil Blunsom · Leon Bottou · Volodymyr Mnih · Chen-Yu Lee · Rich M Schwartz -
2014 Workshop: OPT2014: Optimization for Machine Learning »
Zaid Harchaoui · Suvrit Sra · Alekh Agarwal · Martin Jaggi · Miro Dudik · Aaditya Ramdas · Jean Lasserre · Yoshua Bengio · Amir Beck -
2014 Poster: Gibbs-type Indian Buffet Processes »
Creighton Heaukulani · Daniel Roy -
2014 Poster: Modeling Deep Temporal Dependencies with Recurrent "Grammar Cells" »
Vincent Michalski · Roland Memisevic · Kishore Konda -
2014 Poster: QUIC & DIRTY: A Quadratic Approximation Approach for Dirty Statistical Models »
Cho-Jui Hsieh · Inderjit Dhillon · Pradeep Ravikumar · Stephen Becker · Peder A Olsen -
2014 Poster: How transferable are features in deep neural networks? »
Jason Yosinski · Jeff Clune · Yoshua Bengio · Hod Lipson -
2014 Poster: Consistent Binary Classification with Generalized Performance Metrics »
Sanmi Koyejo · Nagarajan Natarajan · Pradeep Ravikumar · Inderjit Dhillon -
2014 Poster: Efficient Structured Matrix Rank Minimization »
Adams Wei Yu · Wanli Ma · Yaoliang Yu · Jaime Carbonell · Suvrit Sra -
2014 Poster: Fast Prediction for Large-Scale Kernel Machines »
Cho-Jui Hsieh · Si Si · Inderjit Dhillon -
2014 Poster: Identifying and attacking the saddle point problem in high-dimensional non-convex optimization »
Yann N Dauphin · Razvan Pascanu · Caglar Gulcehre · Kyunghyun Cho · Surya Ganguli · Yoshua Bengio -
2014 Poster: Multi-Scale Spectral Decomposition of Massive Graphs »
Si Si · Donghyuk Shin · Inderjit Dhillon · Beresford N Parlett -
2014 Poster: Sparse Random Feature Algorithm as Coordinate Descent in Hilbert Space »
Ian En-Hsu Yen · Ting-Wei Lin · Shou-De Lin · Pradeep Ravikumar · Inderjit Dhillon -
2014 Spotlight: Consistent Binary Classification with Generalized Performance Metrics »
Sanmi Koyejo · Nagarajan Natarajan · Pradeep Ravikumar · Inderjit Dhillon -
2014 Poster: Generative Adversarial Nets »
Ian Goodfellow · Jean Pouget-Abadie · Mehdi Mirza · Bing Xu · David Warde-Farley · Sherjil Ozair · Aaron Courville · Yoshua Bengio -
2014 Poster: On the Number of Linear Regions of Deep Neural Networks »
Guido F Montufar · Razvan Pascanu · Kyunghyun Cho · Yoshua Bengio -
2014 Poster: Proximal Quasi-Newton for Computationally Intensive L1-regularized M-estimators »
Kai Zhong · Ian En-Hsu Yen · Inderjit Dhillon · Pradeep Ravikumar -
2014 Demonstration: Neural Machine Translation »
Bart van Merriënboer · Kyunghyun Cho · Dzmitry Bahdanau · Yoshua Bengio -
2014 Oral: How transferable are features in deep neural networks? »
Jason Yosinski · Jeff Clune · Yoshua Bengio · Hod Lipson -
2014 Poster: Capturing Semantically Meaningful Word Dependencies with an Admixture of Poisson MRFs »
David I Inouye · Pradeep Ravikumar · Inderjit Dhillon -
2014 Poster: Constant Nullspace Strong Convexity and Fast Convergence of Proximal Methods under High-Dimensional Settings »
Ian En-Hsu Yen · Cho-Jui Hsieh · Pradeep Ravikumar · Inderjit Dhillon -
2014 Poster: Expectation Backpropagation: Parameter-Free Training of Multilayer Neural Networks with Continuous or Discrete Weights »
Daniel Soudry · Itay Hubara · Ron Meir -
2014 Poster: Iterative Neural Autoregressive Distribution Estimator NADE-k »
Tapani Raiko · Yao Li · Kyunghyun Cho · Yoshua Bengio -
2014 Poster: Mondrian Forests: Efficient Online Random Forests »
Balaji Lakshminarayanan · Daniel Roy · Yee Whye Teh -
2013 Workshop: Deep Learning »
Yoshua Bengio · Hugo Larochelle · Russ Salakhutdinov · Tomas Mikolov · Matthew D Zeiler · David Mcallester · Nando de Freitas · Josh Tenenbaum · Jian Zhou · Volodymyr Mnih -
2013 Workshop: Output Representation Learning »
Yuhong Guo · Dale Schuurmans · Richard Zemel · Samy Bengio · Yoshua Bengio · Li Deng · Dan Roth · Kilian Q Weinberger · Jason Weston · Kihyuk Sohn · Florent Perronnin · Gabriel Synnaeve · Pablo R Strasser · julien audiffren · Carlo Ciliberto · Dan Goldwasser -
2013 Poster: Action from Still Image Dataset and Inverse Optimal Control to Learn Task Specific Visual Scanpaths »
Stefan Mathe · Cristian Sminchisescu -
2013 Poster: DeViSE: A Deep Visual-Semantic Embedding Model »
Andrea Frome · Greg Corrado · Jonathon Shlens · Samy Bengio · Jeff Dean · Marc'Aurelio Ranzato · Tomas Mikolov -
2013 Poster: BIG & QUIC: Sparse Inverse Covariance Estimation for a Million Variables »
Cho-Jui Hsieh · Matyas A Sustik · Inderjit Dhillon · Pradeep Ravikumar · Russell Poldrack -
2013 Oral: BIG & QUIC: Sparse Inverse Covariance Estimation for a Million Variables »
Cho-Jui Hsieh · Matyas A Sustik · Inderjit Dhillon · Pradeep Ravikumar · Russell Poldrack -
2013 Poster: Multi-Prediction Deep Boltzmann Machines »
Ian Goodfellow · Mehdi Mirza · Aaron Courville · Yoshua Bengio -
2013 Poster: Large Scale Distributed Sparse Precision Estimation »
Huahua Wang · Arindam Banerjee · Cho-Jui Hsieh · Pradeep Ravikumar · Inderjit Dhillon -
2013 Poster: Generalized Denoising Auto-Encoders as Generative Models »
Yoshua Bengio · Li Yao · Guillaume Alain · Pascal Vincent -
2013 Poster: Learning with Noisy Labels »
Nagarajan Natarajan · Inderjit Dhillon · Pradeep Ravikumar · Ambuj Tewari -
2013 Poster: Stochastic Ratio Matching of RBMs for Sparse High-Dimensional Inputs »
Yann Dauphin · Yoshua Bengio -
2013 Poster: Flexible sampling of discrete data correlations without the marginal distributions »
Alfredo Kalaitzis · Ricardo Silva -
2013 Demonstration: Di-BOSS™: Digital Building Operating System Solution »
Jessica Forde · Vivek Rathod · Hooshmand Shookri · Vaibhav Bandari · Ashwath Rajan · John Min · Ariel Fan · Leon Wu · Ashish Gagneja · Doug Riecken · David Solomon · Lauren Hannah · Albert Boulanger · Roger Anderson -
2013 Poster: Blind Calibration in Compressed Sensing using Message Passing Algorithms »
Christophe Schulke · Francesco Caltagirone · Florent Krzakala · Lenka Zdeborová -
2013 Poster: Buy-in-Bulk Active Learning »
Liu Yang · Jaime Carbonell -
2013 Session: Session Chair »
Daniel Roy -
2013 Session: Tutorial Session B »
Daniel Roy -
2012 Workshop: Deep Learning and Unsupervised Feature Learning »
Yoshua Bengio · James Bergstra · Quoc V. Le -
2012 Workshop: Probabilistic Programming: Foundations and Applications (2 day) »
Vikash Mansinghka · Daniel Roy · Noah Goodman -
2012 Workshop: Big Data Meets Computer Vision: First International Workshop on Large Scale Visual Recognition and Retrieval »
Jia Deng · Samy Bengio · Yuanqing Lin · Li Fei-Fei -
2012 Workshop: Probabilistic Programming: Foundations and Applications (2 day) »
Vikash Mansinghka · Daniel Roy · Noah Goodman -
2012 Poster: Bayesian models for Large-scale Hierarchical Classification »
Siddharth Gopal · Yiming Yang · Bing Bai · Alexandru Niculescu-Mizil -
2012 Poster: Training sparse natural image models with a fast Gibbs sampler of an extended state space »
Lucas Theis · Jascha Sohl-Dickstein · Matthias Bethge -
2012 Poster: Random function priors for exchangeable graphs and arrays »
James R Lloyd · Daniel Roy · Peter Orbanz · Zoubin Ghahramani -
2012 Poster: A Divide-and-Conquer Method for Sparse Inverse Covariance Estimation »
Cho-Jui Hsieh · Inderjit Dhillon · Pradeep Ravikumar · Arindam Banerjee -
2011 Workshop: Big Learning: Algorithms, Systems, and Tools for Learning at Scale »
Joseph E Gonzalez · Sameer Singh · Graham Taylor · James Bergstra · Alice Zheng · Misha Bilenko · Yucheng Low · Yoshua Bengio · Michael Franklin · Carlos Guestrin · Andrew McCallum · Alexander Smola · Michael Jordan · Sugato Basu -
2011 Workshop: Deep Learning and Unsupervised Feature Learning »
Yoshua Bengio · Adam Coates · Yann LeCun · Nicolas Le Roux · Andrew Y Ng -
2011 Oral: The Manifold Tangent Classifier »
Salah Rifai · Yann N Dauphin · Pascal Vincent · Yoshua Bengio · Xavier Muller -
2011 Poster: Complexity of Inference in Latent Dirichlet Allocation »
David Sontag · Daniel Roy -
2011 Poster: Shallow vs. Deep Sum-Product Networks »
Olivier Delalleau · Yoshua Bengio -
2011 Poster: The Manifold Tangent Classifier »
Salah Rifai · Yann N Dauphin · Pascal Vincent · Yoshua Bengio · Xavier Muller -
2011 Spotlight: Complexity of Inference in Latent Dirichlet Allocation »
David Sontag · Daniel Roy -
2011 Poster: Greedy Algorithms for Structurally Constrained High Dimensional Problems »
Ambuj Tewari · Pradeep Ravikumar · Inderjit Dhillon -
2011 Poster: Sparse Inverse Covariance Matrix Estimation Using Quadratic Approximation »
Cho-Jui Hsieh · Matyas A Sustik · Inderjit Dhillon · Pradeep Ravikumar -
2011 Poster: Algorithms for Hyper-Parameter Optimization »
James Bergstra · Rémi Bardenet · Yoshua Bengio · Balázs Kégl -
2011 Poster: Nearest Neighbor based Greedy Coordinate Descent »
Inderjit Dhillon · Pradeep Ravikumar · Ambuj Tewari -
2011 Poster: On Tracking The Partition Function »
Guillaume Desjardins · Aaron Courville · Yoshua Bengio -
2011 Poster: Orthogonal Matching Pursuit with Replacement »
Prateek Jain · Ambuj Tewari · Inderjit Dhillon -
2010 Workshop: Deep Learning and Unsupervised Feature Learning »
Honglak Lee · Marc'Aurelio Ranzato · Yoshua Bengio · Geoffrey E Hinton · Yann LeCun · Andrew Y Ng -
2010 Spotlight: Guaranteed Rank Minimization via Singular Value Projection »
Prateek Jain · Raghu Meka · Inderjit Dhillon -
2010 Poster: Label Embedding Trees for Large Multi-Class Tasks »
Samy Bengio · Jason E Weston · David Grangier -
2010 Poster: Guaranteed Rank Minimization via Singular Value Projection »
Prateek Jain · Raghu Meka · Inderjit Dhillon -
2010 Spotlight: Inductive Regularized Learning of Kernel Functions »
Prateek Jain · Brian Kulis · Inderjit Dhillon -
2010 Poster: Inductive Regularized Learning of Kernel Functions »
Prateek Jain · Brian Kulis · Inderjit Dhillon -
2009 Poster: Slow, Decorrelated Features for Pretraining Complex Cell-like Networks »
James Bergstra · Yoshua Bengio -
2009 Poster: An Infinite Factor Model Hierarchy Via a Noisy-Or Mechanism »
Aaron Courville · Douglas Eck · Yoshua Bengio -
2009 Poster: Group Sparse Coding »
Samy Bengio · Fernando Pereira · Yoram Singer · Dennis Strelow -
2009 Session: Debate on Future Publication Models for the NIPS Community »
Yoshua Bengio -
2009 Poster: An Online Algorithm for Large Scale Image Similarity Learning »
Gal Chechik · Uri Shalit · Varun Sharma · Samy Bengio -
2009 Poster: Matrix Completion from Power-Law Distributed Samples »
Raghu Meka · Prateek Jain · Inderjit Dhillon -
2008 Workshop: Probabilistic Programming: Universal Languages, Systems and Applications »
Daniel Roy · John Winn · David A McAllester · Vikash Mansinghka · Josh Tenenbaum -
2008 Oral: The Mondrian Process »
Daniel Roy · Yee Whye Teh -
2008 Poster: The Mondrian Process »
Daniel Roy · Yee Whye Teh -
2008 Poster: Online Metric Learning and Fast Similarity Search »
Prateek Jain · Brian Kulis · Inderjit Dhillon · Kristen Grauman -
2008 Oral: Online Metric Learning and Fast Similarity Search »
Prateek Jain · Brian Kulis · Inderjit Dhillon · Kristen Grauman -
2007 Workshop: Efficient Machine Learning - Overcoming Computational Bottlenecks in Machine Learning (Part 2) »
Samy Bengio · Corinna Cortes · Dennis DeCoste · Francois Fleuret · Ramesh Natarajan · Edwin Pednault · Dan Pelleg · Elad Yom-Tov -
2007 Workshop: Efficient Machine Learning - Overcoming Computational Bottlenecks in Machine Learning (Part 1) »
Samy Bengio · Corinna Cortes · Dennis DeCoste · Francois Fleuret · Ramesh Natarajan · Edwin Pednault · Dan Pelleg · Elad Yom-Tov -
2007 Spotlight: Nearest-Neighbor-Based Active Learning for Rare Category Detection »
Jingrui He · Jaime Carbonell -
2007 Poster: Bayesian Agglomerative Clustering with Coalescents »
Yee Whye Teh · Hal Daumé III · Daniel Roy -
2007 Poster: Augmented Functional Time Series Representation and Forecasting with Gaussian Processes »
Nicolas Chapados · Yoshua Bengio -
2007 Poster: Nearest-Neighbor-Based Active Learning for Rare Category Detection »
Jingrui He · Jaime Carbonell -
2007 Poster: Learning the 2-D Topology of Images »
Nicolas Le Roux · Yoshua Bengio · Pascal Lamblin · Marc Joliveau · Balázs Kégl -
2007 Spotlight: Augmented Functional Time Series Representation and Forecasting with Gaussian Processes »
Nicolas Chapados · Yoshua Bengio -
2007 Oral: Bayesian Agglomerative Clustering with Coalescents »
Yee Whye Teh · Hal Daumé III · Daniel Roy -
2007 Poster: Topmoumoute Online Natural Gradient Algorithm »
Nicolas Le Roux · Pierre-Antoine Manzagol · Yoshua Bengio -
2006 Workshop: Learning to Compare Examples »
David Grangier · Samy Bengio -
2006 Poster: Learning annotated hierarchies from relational data »
Daniel Roy · Charles Kemp · Vikash Mansinghka · Josh Tenenbaum -
2006 Poster: Greedy Layer-Wise Training of Deep Networks »
Yoshua Bengio · Pascal Lamblin · Dan Popovici · Hugo Larochelle -
2006 Talk: Greedy Layer-Wise Training of Deep Networks »
Yoshua Bengio · Pascal Lamblin · Dan Popovici · Hugo Larochelle -
2006 Talk: Learning annotated hierarchies from relational data »
Daniel Roy · Charles Kemp · Vikash Mansinghka · Josh Tenenbaum -
2006 Poster: Differential Entropic Clustering of Multivariate Gaussians »
Jason V Davis · Inderjit Dhillon