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Author Information
Jonathan Scarlett (National University of Singapore)
Piotr Indyk (MIT)
Ali Vakilian (University of Wisconsin-Madison)
Adrian Weller (Cambridge, Alan Turing Institute)
Adrian Weller is Programme Director for AI at The Alan Turing Institute, the UK national institute for data science and AI, where he is also a Turing Fellow leading work on safe and ethical AI. He is a Principal Research Fellow in Machine Learning at the University of Cambridge, and at the Leverhulme Centre for the Future of Intelligence where he is Programme Director for Trust and Society. His interests span AI, its commercial applications and helping to ensure beneficial outcomes for society. He serves on several boards including the Centre for Data Ethics and Innovation. Previously, Adrian held senior roles in finance.
Partha P Mitra (Cold Spring Harbor Laboratory)
Benjamin Aubin (Ipht Saclay)
Bruno Loureiro (IPhT Saclay)
Florent Krzakala (ENS Paris & Sorbonnes Université)
Lenka Zdeborová (CEA)
Kristina Monakhova (UC Berkeley)
Joshua Yurtsever (University of California Berkeley)
Laura Waller (UC Berkeley)
Hendrik Sommerhoff (University of Siegen)
Michael Moeller (University of Siegen)
Rushil Anirudh (Lawrence Livermore National Laboratory)
Shuang Qiu (University of Michigan)
Xiaohan Wei (University of Southern California)
Zhuoran Yang (Princeton University)
Jayaraman Thiagarajan (Lawrence Livermore National Labs)
Salman Asif (University of California, Riverside)
Michael Gillhofer (LIT AI Lab, Institute for Machine Learning, Johannes Kepler University Linz, Austria)
Johannes Brandstetter (LIT AI Lab / University Linz)
Sepp Hochreiter (LIT AI Lab / University Linz / IARAI)
Felix Petersen (University of Konstanz)
Dhruv Patel (University of Southern California)
Assad Oberai (University of Southern California)
Akshay Kamath (The University of Texas at Austin)
Sushrut Karmalkar (The University of Texas at Austin)
Eric Price (University of Texas at Austin)
Ali Ahmed (Information Technology University)
Zahra Kadkhodaie (New York University)
Sreyas Mohan (NYU)
Eero Simoncelli (HHMI / New York University)
Eero P. Simoncelli received the B.S. degree in Physics in 1984 from Harvard University, studied applied mathematics at Cambridge University for a year and a half, and then received the M.S. degree in 1988 and the Ph.D. degree in 1993, both in Electrical Engineering from the Massachusetts Institute of Technology. He was an Assistant Professor in the Computer and Information Science department at the University of Pennsylvania from 1993 until 1996. He moved to New York University in September of 1996, where he is currently a Professor in Neural Science, Mathematics, and Psychology. In August 2000, he became an Associate Investigator of the Howard Hughes Medical Institute, under their new program in Computational Biology. In Fall 2020, he resigned his HHMI appointment to become the scientific director of the Center for Computational Neuroscience at the Flatiron Institute, of the Simons Foundation. His research interests span a wide range of topics in the representation and analysis of visual images, in both machine and biological systems.
Carlos Fernandez-Granda (NYU)
Oscar Leong (Rice University)
Wesam Sakla (Lawrence Livermore National Laboratory)
Rebecca Willett (U Chicago)
Stephan Hoyer (Google Research)
Jascha Sohl-Dickstein (Google Brain)
Sam Greydanus (Oregon State University)
I am a recent graduate of Dartmouth College, where I majored in physics and dabbled in everything else. I have interned at CERN, Microsoft Azure, and the DARPA Explainable AI Project. I like to use memory-based models to generate sequences and policies. So far, I have used them to approximate the Enigma cipher, generate realistic handwriting, and visualize how reinforcement-learning agents play Atari games. One of my priorities as a scientist is to explain my work clearly and make it easy to replicate.
Gauri Jagatap (Iowa State University)
Graduate student at Iowa State University
Chinmay Hegde (Iowa State University)
Michael Kellman (University of California Berkeley)
I am a PhD graduate student at UC Berkeley in the EECS department, where I work on problems in the fields of signal processing, computational imaging, and machine learning. I am advised by Prof. Laura Waller and Prof. Michael Lustig and am funded by NSF GRFP. I am also affiliated with the Berkeley Artificial Intelligence Research Laboratory and the Berkeley Center for Computational Imaging. In broadest terms, the goal of my research is to improve the limitation of modern computational imaging systems through data-driven design. I'm particularly interested in the areas of signal processing, machine learning theory, image reconstruction algorithms, and optical modeling. Specifically, my work is focused on the applications of microscopy, medical imaging, and photography.
Jonathan Tamir (University of California, Berkeley)
Nouamane Laanait (Oak Ridge National Laboratory)
Ousmane Dia (Element AI)
Mirco Ravanelli (Montreal Istitute for Learning Algorithms)
I received my master's degree in Telecommunications Engineering (full marks and honours) from the University of Trento, Italy in 2011. I then joined the SHINE research group (led by Prof. Maurizio Omologo) of the Bruno Kessler Foundation (FBK), contributing to some projects on distant-talking speech recognition in noisy and reverberant environments, such as DIRHA and DOMHOS. In 2013 I was visiting researcher at the International Computer Science Institute (University of California, Berkeley) working on deep neural networks for large-vocabulary speech recognition in the context of the IARPA BABEL project (led by Prof. Nelson Morgan). I received my PhD (with cum laude distinction) in Information and Communication Technology from the University of Trento in December 2017. During my PhD I worked on “deep learning for distant speech recognition”, with a particular focus on recurrent and cooperative neural networks (see my PhD thesis here). In the context of my PhD I recently spent 6 months in the MILA lab led by Prof. Yoshua Bengio. I'm currently a post-doc researcher at the University of Montreal, working on deep learning for speech recognition in the MILA Lab.
Jonathan Binas (Mila, Montreal)
Negar Rostamzadeh (Elemenet AI)
Shirin Jalali (Nokia Bell Labs)
Tiantian Fang (University of Illinois Urbana-Champaign)
Alex Schwing (University of Illinois at Urbana-Champaign)
Sébastien Lachapelle (Mila, Université de Montréal)
Philippe Brouillard (Université de Montréal)
Tristan Deleu (Mila - Universite de Montreal)
Simon Lacoste-Julien (Mila, Université de Montréal)
Simon Lacoste-Julien is an associate professor at Mila and DIRO from Université de Montréal, and Canada CIFAR AI Chair holder. He also heads part time the SAIT AI Lab Montreal from Samsung. His research interests are machine learning and applied math, with applications in related fields like computer vision and natural language processing. He obtained a B.Sc. in math., physics and computer science from McGill, a PhD in computer science from UC Berkeley and a post-doc from the University of Cambridge. He spent a few years as a research faculty at INRIA and École normale supérieure in Paris before coming back to his roots in Montreal in 2016 to answer the call from Yoshua Bengio in growing the Montreal AI ecosystem.
Stella Yu (UC Berkeley / ICSI)
Arya Mazumdar (University of Massachusetts Amherst)
Ankit Singh Rawat (Google Research)
Yue Zhao (Stony Brook University)
Jianshu Chen (Tencent AI Lab)
Xiaoyang Li (University of Houston)
Hubert Ramsauer (LIT AI Lab / University Linz)
Gabrio Rizzuti (Georgia Institute of Technology)
Nikolaos Mitsakos (Anadarko Petroleum - OXY)
Dingzhou Cao (Occidental)
Thomas Strohmer (University of California, Davis)
Yang Li (Facebook)
Pei Peng (Rutgers, the State University of New Jersey)
Gregory Ongie (University of Chicago)
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2021 Poster: Impression learning: Online representation learning with synaptic plasticity »
Colin Bredenberg · Benjamin Lyo · Eero Simoncelli · Cristina Savin -
2020 : Orals 2.2: Hardware Beyond Backpropagation: a Photonic Co-Processor for Direct Feedback Alignmen »
Julien Launay · Iacopo Poli · Laurent Daudet · Florent Krzakala -
2020 : Traffic Map Movies - An Introduction to the Traffic4cast Challenge »
Sepp Hochreiter -
2020 : Invited talk - Towards robust self-supervised learning of speech representations »
Mirco Ravanelli -
2020 : Session 3 | Invited talk: Laura Waller, "Physics-based Learning for Computational Microscopy" »
Laura Waller · Atilim Gunes Baydin -
2020 : Reverse engineering learned optimizers reveals known and novel mechanisms »
Niru Maheswaranathan · David Sussillo · Luke Metz · Ruoxi Sun · Jascha Sohl-Dickstein -
2020 : Rebecca Willett - Model Adaptation for Inverse Problems in Imaging »
Rebecca Willett -
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 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: Privacy Preserving Machine Learning - PriML and PPML Joint Edition »
Borja Balle · James Bell · Aurélien Bellet · Kamalika Chaudhuri · Adria Gascon · Antti Honkela · Antti Koskela · Casey Meehan · Olga Ohrimenko · Mi Jung Park · Mariana Raykova · Mary Anne Smart · Yu-Xiang Wang · Adrian Weller -
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 Poster: Direct Feedback Alignment Scales to Modern Deep Learning Tasks and Architectures »
Julien Launay · Iacopo Poli · François Boniface · Florent Krzakala -
2020 Poster: Not All Unlabeled Data are Equal: Learning to Weight Data in Semi-supervised Learning »
Zhongzheng Ren · Raymond A. Yeh · Alex Schwing -
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: Generalization error in high-dimensional perceptrons: Approaching Bayes error with convex optimization »
Benjamin Aubin · Florent Krzakala · Yue Lu · Lenka Zdeborová -
2020 Poster: A Statistical Mechanics Framework for Task-Agnostic Sample Design in Machine Learning »
Bhavya Kailkhura · Jayaraman Thiagarajan · Qunwei Li · Jize Zhang · Yi Zhou · Timo Bremer -
2020 Poster: Towards a Better Global Loss Landscape of GANs »
Ruoyu Sun · Tiantian Fang · Alex Schwing -
2020 Poster: Inverting Gradients - How easy is it to break privacy in federated learning? »
Jonas Geiping · Hartmut Bauermeister · Hannah Dröge · Michael Moeller -
2020 Poster: Learning efficient task-dependent representations with synaptic plasticity »
Colin Bredenberg · Eero Simoncelli · Cristina Savin -
2020 Oral: Towards a Better Global Loss Landscape of GANs »
Ruoyu Sun · Tiantian Fang · Alex Schwing -
2020 Session: Orals & Spotlights Track 22: Vision Applications »
Leonid Sigal · Alex Schwing -
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: Reservoir Computing meets Recurrent Kernels and Structured Transforms »
Jonathan Dong · Ruben Ohana · Mushegh Rafayelyan · Florent Krzakala -
2020 Poster: Ode to an ODE »
Krzysztof Choromanski · Jared Quincy Davis · Valerii Likhosherstov · Xingyou Song · Jean-Jacques Slotine · Jacob Varley · Honglak Lee · Adrian Weller · Vikas Sindhwani -
2020 Poster: Adversarial Example Games »
Joey Bose · Gauthier Gidel · Hugo Berard · Andre Cianflone · Pascal Vincent · Simon Lacoste-Julien · Will Hamilton -
2020 Poster: Differentiable Causal Discovery from Interventional Data »
Philippe Brouillard · Sébastien Lachapelle · Alexandre Lacoste · Simon Lacoste-Julien · Alexandre Drouin -
2020 Poster: Removing Bias in Multi-modal Classifiers: Regularization by Maximizing Functional Entropies »
Itai Gat · Idan Schwartz · Alex Schwing · Tamir Hazan -
2020 Poster: Early-Learning Regularization Prevents Memorization of Noisy Labels »
Sheng Liu · Jonathan Niles-Weed · Narges Razavian · Carlos Fernandez-Granda -
2020 Spotlight: Differentiable Causal Discovery from Interventional Data »
Philippe Brouillard · Sébastien Lachapelle · Alexandre Lacoste · Simon Lacoste-Julien · Alexandre Drouin -
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 Oral: Reservoir Computing meets Recurrent Kernels and Structured Transforms »
Jonathan Dong · Ruben Ohana · Mushegh Rafayelyan · Florent Krzakala -
2020 Poster: O(n) Connections are Expressive Enough: Universal Approximability of Sparse Transformers »
Chulhee Yun · Yin-Wen Chang · Srinadh Bhojanapalli · Ankit Singh Rawat · Sashank Reddi · Sanjiv Kumar -
2020 Poster: Robust large-margin learning in hyperbolic space »
Melanie Weber · Manzil Zaheer · Ankit Singh Rawat · Aditya Menon · Sanjiv Kumar -
2020 Poster: High-Throughput Synchronous Deep RL »
Iou-Jen Liu · Raymond A. Yeh · Alex Schwing -
2020 Poster: Phase retrieval in high dimensions: Statistical and computational phase transitions »
Antoine Maillard · Bruno Loureiro · Florent Krzakala · Lenka Zdeborová -
2020 Poster: Dynamical mean-field theory for stochastic gradient descent in Gaussian mixture classification »
Francesca Mignacco · Florent Krzakala · Pierfrancesco Urbani · Lenka Zdeborová -
2020 Poster: Complex Dynamics in Simple Neural Networks: Understanding Gradient Flow in Phase Retrieval »
Stefano Sarao Mannelli · Giulio Biroli · Chiara Cammarota · Florent Krzakala · Pierfrancesco Urbani · Lenka Zdeborová -
2020 Poster: Adversarial robustness via robust low rank representations »
Pranjal Awasthi · Himanshu Jain · Ankit Singh Rawat · Aravindan Vijayaraghavan -
2020 Poster: The Generalized Lasso with Nonlinear Observations and Generative Priors »
Zhaoqiang Liu · Jonathan Scarlett -
2020 Poster: Upper Confidence Primal-Dual Reinforcement Learning for CMDP with Adversarial Loss »
Shuang Qiu · Xiaohan Wei · Zhuoran Yang · Jieping Ye · Zhaoran Wang -
2019 : Poster Session »
Pravish Sainath · Mohamed Akrout · Charles Delahunt · Nathan Kutz · Guangyu Robert Yang · Joseph Marino · L F Abbott · Nicolas Vecoven · Damien Ernst · andrew warrington · Michael Kagan · Kyunghyun Cho · Kameron Harris · Leopold Grinberg · John J. Hopfield · Dmitry Krotov · Taliah Muhammad · Erick Cobos · Edgar Walker · Jacob Reimer · Andreas Tolias · Alexander Ecker · Janaki Sheth · Yu Zhang · Maciej Wołczyk · Jacek Tabor · Szymon Maszke · Roman Pogodin · Dane Corneil · Wulfram Gerstner · Baihan Lin · Guillermo Cecchi · Jenna M Reinen · Irina Rish · Guillaume Bellec · Darjan Salaj · Anand Subramoney · Wolfgang Maass · Yueqi Wang · Ari Pakman · Jin Hyung Lee · Liam Paninski · Bryan Tripp · Colin Graber · Alex Schwing · Luke Prince · Gabriel Ocker · Michael Buice · Benjamin Lansdell · Konrad Kording · Jack Lindsey · Terrence Sejnowski · Matthew Farrell · Eric Shea-Brown · Nicolas Farrugia · Victor Nepveu · Jiwoong Im · Kristin Branson · Brian Hu · Ramakrishnan Iyer · Stefan Mihalas · Sneha Aenugu · Hananel Hazan · Sihui Dai · Tan Nguyen · Doris Tsao · Richard Baraniuk · Anima Anandkumar · Hidenori Tanaka · Aran Nayebi · Stephen Baccus · Surya Ganguli · Dean Pospisil · Eilif Muller · Jeffrey S Cheng · Gaël Varoquaux · Kamalaker Dadi · Dimitrios C Gklezakos · Rajesh PN Rao · Anand Louis · Christos Papadimitriou · Santosh Vempala · Naganand Yadati · Daniel Zdeblick · Daniela M Witten · Nicholas Roberts · Vinay Prabhu · Pierre Bellec · Poornima Ramesh · Jakob H Macke · Santiago Cadena · Guillaume Bellec · Franz Scherr · Owen Marschall · Robert Kim · Hannes Rapp · Marcio Fonseca · Oliver Armitage · Jiwoong Im · Thomas Hardcastle · Abhishek Sharma · Wyeth Bair · Adrian Valente · Shane Shang · Merav Stern · Rutuja Patil · Peter Wang · Sruthi Gorantla · Peter Stratton · Tristan Edwards · Jialin Lu · Martin Ester · Yurii Vlasov · Siavash Golkar -
2019 : Coffee Break + Poster Session II »
Niki Parmar · Haraldur Hallgrimsson · Christian Kames · Arijit Patra · Abdullah-Al-Zubaer Imran · Junlin Yang · David Zimmerer · Arunava Chakravarty · Lawrence Schobs · Alexej Gossmann · TUNG-I CHEN · Tarun Dutt · Li Yao · Octavio Eleazar Martinez Manzanera · Johannes Pinckaers · Mehmet Ufuk Dalmis · Deepak Gupta · Nandinee Haq · David Ruhe · Jevgenij Gamper · Alfredo De Goyeneche Macaya · Jonathan Tamir · Byunghwan Jeon · SUBBAREDDY OOTA · Reinhard Heckel · Pamela K Douglas · Oleksii Sidorov · Ke Wang · Melanie Garcia · Ravi Soni · Ankita Shukla -
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 : Coffee Break & Poster Session 2 »
Juho Lee · Yoonho Lee · Yee Whye Teh · Raymond A. Yeh · Yuan-Ting Hu · Alex Schwing · Sara Ahmadian · Alessandro Epasto · Marina Knittel · Ravi Kumar · Mohammad Mahdian · Christian Bueno · Aditya Sanghi · Pradeep Kumar Jayaraman · Ignacio Arroyo-Fernández · Andrew Hryniowski · Vinayak Mathur · Sanjay Singh · Shahrzad Haddadan · Vasco Portilheiro · Luna Zhang · Mert Yuksekgonul · Jhosimar Arias Figueroa · Deepak Maurya · Balaraman Ravindran · Frank NIELSEN · Philip Pham · Justin Payan · Andrew McCallum · Jinesh Mehta · Ke SUN -
2019 : Traffic4cast -- Traffic Map Movie Forecasting »
Sepp Hochreiter · Leonid Sigal · Moritz Neun · David Jonietz · Sungbin Choi · Henry Martin · Wei Yu · Zhichen Liu · Tu Nguyen · Pedro Herruzo Sánchez · Xiaoxia Shi · Aleksandra Gruca · Alastair Sutherland · David Kreil · Michael Kopp -
2019 : Lenka Zdeborova »
Lenka Zdeborová -
2019 : Contributed Talk - Chirality Nets: Exploiting Structure in Human Pose Regression »
Raymond A. Yeh · Yuan-Ting Hu · Alex Schwing -
2019 : Lunch Break and Posters »
Xingyou Song · Elad Hoffer · Wei-Cheng Chang · Jeremy Cohen · Jyoti Islam · Yaniv Blumenfeld · Andreas Madsen · Jonathan Frankle · Sebastian Goldt · Satrajit Chatterjee · Abhishek Panigrahi · Alex Renda · Brian Bartoldson · Israel Birhane · Aristide Baratin · Niladri Chatterji · Roman Novak · Jessica Forde · YiDing Jiang · Yilun Du · Linara Adilova · Michael Kamp · Berry Weinstein · Itay Hubara · Tal Ben-Nun · Torsten Hoefler · Daniel Soudry · Hsiang-Fu Yu · Kai Zhong · Yiming Yang · Inderjit Dhillon · Jaime Carbonell · Yanqing Zhang · Dar Gilboa · Johannes Brandstetter · Alexander R Johansen · Gintare Karolina Dziugaite · Raghav Somani · Ari Morcos · Freddie Kalaitzis · Hanie Sedghi · Lechao Xiao · John Zech · Muqiao Yang · Simran Kaur · Qianli Ma · Yao-Hung Hubert Tsai · Ruslan Salakhutdinov · Sho Yaida · Zachary Lipton · Daniel Roy · Michael Carbin · Florent Krzakala · Lenka Zdeborová · Guy Gur-Ari · Ethan Dyer · Dilip Krishnan · Hossein Mobahi · Samy Bengio · Behnam Neyshabur · Praneeth Netrapalli · Kris Sankaran · Julien Cornebise · Yoshua Bengio · Vincent Michalski · Samira Ebrahimi Kahou · Md Rifat Arefin · Jiri Hron · Jaehoon Lee · Jascha Sohl-Dickstein · Samuel Schoenholz · David Schwab · Dongyu Li · Sang Keun Choe · Henning Petzka · Ashish Verma · Zhichao Lin · Cristian Sminchisescu -
2019 : Poster Spotlight 2 »
Aaron Sidford · Mengdi Wang · Lin Yang · Yinyu Ye · Zuyue Fu · Zhuoran Yang · Yongxin Chen · Zhaoran Wang · Ofir Nachum · Bo Dai · Ilya Kostrikov · Dale Schuurmans · Ziyang Tang · Yihao Feng · Lihong Li · Denny Zhou · Qiang Liu · Rodrigo Toro Icarte · Ethan Waldie · Toryn Klassen · Rick Valenzano · Margarita Castro · Simon Du · Sham Kakade · Ruosong Wang · Minshuo Chen · Tianyi Liu · Xingguo Li · Zhaoran Wang · Tuo Zhao · Philip Amortila · Doina Precup · Prakash Panangaden · Marc Bellemare -
2019 : Morning Coffee Break & Poster Session »
Eric Metodiev · Keming Zhang · Markus Stoye · Randy Churchill · Soumalya Sarkar · Miles Cranmer · Johann Brehmer · Danilo Jimenez Rezende · Peter Harrington · AkshatKumar Nigam · Nils Thuerey · Lukasz Maziarka · Alvaro Sanchez Gonzalez · Atakan Okan · James Ritchie · N. Benjamin Erichson · Harvey Cheng · Peihong Jiang · Seong Ho Pahng · Samson Koelle · Sami Khairy · Adrian Pol · Rushil Anirudh · Jannis Born · Benjamin Sanchez-Lengeling · Brian Timar · Rhys Goodall · Tamás Kriváchy · Lu Lu · Thomas Adler · Nathaniel Trask · Noëlie Cherrier · Tomohiko Konno · Muhammad Kasim · Tobias Golling · Zaccary Alperstein · Andrei Ustyuzhanin · James Stokes · Anna Golubeva · Ian Char · Ksenia Korovina · Youngwoo Cho · Chanchal Chatterjee · Tom Westerhout · Gorka Muñoz-Gil · Juan Zamudio-Fernandez · Jennifer Wei · Brian Lee · Johannes Kofler · Bruce Power · Nikita Kazeev · Andrey Ustyuzhanin · Artem Maevskiy · Pascal Friederich · Arash Tavakoli · Willie Neiswanger · Bohdan Kulchytskyy · sindhu hari · Paul Leu · Paul Atzberger -
2019 : Poster and Coffee Break 1 »
Aaron Sidford · Aditya Mahajan · Alejandro Ribeiro · Alex Lewandowski · Ali H Sayed · Ambuj Tewari · Angelika Steger · Anima Anandkumar · Asier Mujika · Hilbert J Kappen · Bolei Zhou · Byron Boots · Chelsea Finn · Chen-Yu Wei · Chi Jin · Ching-An Cheng · Christina Yu · Clement Gehring · Craig Boutilier · Dahua Lin · Daniel McNamee · Daniel Russo · David Brandfonbrener · Denny Zhou · Devesh Jha · Diego Romeres · Doina Precup · Dominik Thalmeier · Eduard Gorbunov · Elad Hazan · Elena Smirnova · Elvis Dohmatob · Emma Brunskill · Enrique Munoz de Cote · Ethan Waldie · Florian Meier · Florian Schaefer · Ge Liu · Gergely Neu · Haim Kaplan · Hao Sun · Hengshuai Yao · Jalaj Bhandari · James A Preiss · Jayakumar Subramanian · Jiajin Li · Jieping Ye · Jimmy Smith · Joan Bas Serrano · Joan Bruna · John Langford · Jonathan Lee · Jose A. Arjona-Medina · Kaiqing Zhang · Karan Singh · Yuping Luo · Zafarali Ahmed · Zaiwei Chen · Zhaoran Wang · Zhizhong Li · Zhuoran Yang · Ziping Xu · Ziyang Tang · Yi Mao · David Brandfonbrener · Shirli Di-Castro · Riashat Islam · Zuyue Fu · Abhishek Naik · Saurabh Kumar · Benjamin Petit · Angeliki Kamoutsi · Simone Totaro · Arvind Raghunathan · Rui Wu · Donghwan Lee · Dongsheng Ding · Alec Koppel · Hao Sun · Christian Tjandraatmadja · Mahdi Karami · Jincheng Mei · Chenjun Xiao · Junfeng Wen · Zichen Zhang · Ross Goroshin · Mohammad Pezeshki · Jiaqi Zhai · Philip Amortila · Shuo Huang · Mariya Vasileva · El houcine Bergou · Adel Ahmadyan · Haoran Sun · Sheng Zhang · Lukas Gruber · Yuanhao Wang · Tetiana Parshakova -
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 Workshop: Bridging Game Theory and Deep Learning »
Ioannis Mitliagkas · Gauthier Gidel · Niao He · Reyhane Askari Hemmat · N H · Nika Haghtalab · Simon Lacoste-Julien -
2019 Workshop: Privacy in Machine Learning (PriML) »
Borja Balle · Kamalika Chaudhuri · Antti Honkela · Antti Koskela · Casey Meehan · Mi Jung Park · Mary Anne Smart · Mary Anne Smart · Adrian Weller -
2019 : Poster Session »
Lili Yu · Aleksei Kroshnin · Alex Delalande · Andrew Carr · Anthony Tompkins · Aram-Alexandre Pooladian · Arnaud Robert · Ashok Vardhan Makkuva · Aude Genevay · Bangjie Liu · Bo Zeng · Charlie Frogner · Elsa Cazelles · Esteban G Tabak · Fabio Ramos · François-Pierre PATY · Georgios Balikas · Giulio Trigila · Hao Wang · Hinrich Mahler · Jared Nielsen · Karim Lounici · Kyle Swanson · Mukul Bhutani · Pierre Bréchet · Piotr Indyk · samuel cohen · Stefanie Jegelka · Tao Wu · Thibault Sejourne · Tudor Manole · Wenjun Zhao · Wenlin Wang · Wenqi Wang · Yonatan Dukler · Zihao Wang · Chaosheng Dong -
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 : Local gain control and perceptual invariances »
Eero Simoncelli -
2019 : Posters »
Colin Graber · Yuan-Ting Hu · Tiantian Fang · Jessica Hamrick · Giorgio Giannone · John Co-Reyes · Boyang Deng · Eric Crawford · Andrea Dittadi · Peter Karkus · Matthew Dirks · Rakshit Trivedi · Sunny Raj · Javier Felip Leon · Harris Chan · Jan Chorowski · Jeff Orchard · Aleksandar Stanić · Adam Kortylewski · Ben Zinberg · Chenghui Zhou · Wei Sun · Vikash Mansinghka · Chun-Liang Li · Marco Cusumano-Towner -
2019 : Learning-Based Low-Rank Approximations »
Piotr Indyk -
2019 : Neural Reparameterization Improves Structural Optimization »
Stephan Hoyer · Jascha Sohl-Dickstein · Sam Greydanus -
2019 : Computational microscopy in scattering media »
Laura Waller -
2019 : Robust One-Bit Recovery via ReLU Generative Networks: Improved Statistical Rate and Global Landscape Analysis »
Shuang Qiu · Xiaohan Wei · Zhuoran Yang -
2019 : The spiked matrix model with generative priors »
Lenka Zdeborová -
2019 Workshop: Workshop on Human-Centric Machine Learning »
Plamen P Angelov · Nuria Oliver · Adrian Weller · Manuel Rodriguez · Isabel Valera · Silvia Chiappa · Hoda Heidari · Niki Kilbertus -
2019 Poster: Chirality Nets for Human Pose Regression »
Raymond A. Yeh · Yuan-Ting Hu · Alex Schwing -
2019 Poster: Graph Structured Prediction Energy Networks »
Colin Graber · Alex Schwing -
2019 Poster: Superset Technique for Approximate Recovery in One-Bit Compressed Sensing »
Larkin Flodin · Venkata Gandikota · Arya Mazumdar -
2019 Poster: Sample Complexity of Learning Mixture of Sparse Linear Regressions »
Akshay Krishnamurthy · Arya Mazumdar · Andrew McGregor · Soumyabrata Pal -
2019 Poster: Algorithmic Guarantees for Inverse Imaging with Untrained Network Priors »
Gauri Jagatap · Chinmay Hegde -
2019 Poster: Hamiltonian Neural Networks »
Sam Greydanus · Misko Dzamba · Jason Yosinski -
2019 Poster: Reducing Noise in GAN Training with Variance Reduced Extragradient »
Tatjana Chavdarova · Gauthier Gidel · François Fleuret · Simon Lacoste-Julien -
2019 Poster: Estimating Entropy of Distributions in Constant Space »
Jayadev Acharya · Sourbh Bhadane · Piotr Indyk · Ziteng Sun -
2019 Poster: The spiked matrix model with generative priors »
Benjamin Aubin · Bruno Loureiro · Antoine Maillard · Florent Krzakala · Lenka Zdeborová -
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: Leader Stochastic Gradient Descent for Distributed Training of Deep Learning Models »
Yunfei Teng · Wenbo Gao · François Chalus · Anna Choromanska · Donald Goldfarb · Adrian Weller -
2019 Poster: Statistical-Computational Tradeoff in Single Index Models »
Lingxiao Wang · Zhuoran Yang · Zhaoran Wang -
2019 Poster: RUDDER: Return Decomposition for Delayed Rewards »
Jose A. Arjona-Medina · Michael Gillhofer · Michael Widrich · Thomas Unterthiner · Johannes Brandstetter · Sepp Hochreiter -
2019 Poster: Flexible information routing in neural populations through stochastic comodulation »
Caroline Haimerl · Cristina Savin · Eero Simoncelli -
2019 Poster: Adaptive Cross-Modal Few-shot Learning »
Chen Xing · Negar Rostamzadeh · Boris Oreshkin · Pedro O. Pinheiro -
2019 Poster: Data-driven Estimation of Sinusoid Frequencies »
Gautier Izacard · Sreyas Mohan · Carlos Fernandez-Granda -
2019 Poster: Provably Global Convergence of Actor-Critic: A Case for Linear Quadratic Regulator with Ergodic Cost »
Zhuoran Yang · Yongxin Chen · Mingyi Hong · Zhaoran Wang -
2019 Poster: Stochastic Variance Reduced Primal Dual Algorithms for Empirical Composition Optimization »
Adithya M Devraj · Jianshu Chen -
2019 Poster: Neural Proximal/Trust Region Policy Optimization Attains Globally Optimal Policy »
Boyi Liu · Qi Cai · Zhuoran Yang · Zhaoran Wang -
2019 Poster: Neural Temporal-Difference Learning Converges to Global Optima »
Qi Cai · Zhuoran Yang · Jason Lee · Zhaoran Wang -
2019 Poster: Time/Accuracy Tradeoffs for Learning a ReLU with respect to Gaussian Marginals »
Surbhi Goel · Sushrut Karmalkar · Adam Klivans -
2019 Poster: Multilabel reductions: what is my loss optimising? »
Aditya Menon · Ankit Singh Rawat · Sashank Reddi · Sanjiv Kumar -
2019 Spotlight: Multilabel reductions: what is my loss optimising? »
Aditya Menon · Ankit Singh Rawat · Sashank Reddi · Sanjiv Kumar -
2019 Spotlight: Time/Accuracy Tradeoffs for Learning a ReLU with respect to Gaussian Marginals »
Surbhi Goel · Sushrut Karmalkar · Adam Klivans -
2019 Poster: Learning Erdos-Renyi Random Graphs via Edge Detecting Queries »
Zihan Li · Matthias Fresacher · Jonathan Scarlett -
2019 Poster: Variance Reduced Policy Evaluation with Smooth Function Approximation »
Hoi-To Wai · Mingyi Hong · Zhuoran Yang · Zhaoran Wang · Kexin Tang -
2019 Poster: Neural Multisensory Scene Inference »
Jae Hyun Lim · Pedro O. Pinheiro · Negar Rostamzadeh · Chris Pal · Sungjin Ahn -
2019 Poster: Outlier-Robust High-Dimensional Sparse Estimation via Iterative Filtering »
Ilias Diakonikolas · Daniel Kane · Sushrut Karmalkar · Eric Price · Alistair Stewart -
2019 Poster: Policy Optimization Provably Converges to Nash Equilibria in Zero-Sum Linear Quadratic Games »
Kaiqing Zhang · Zhuoran Yang · Tamer Basar -
2019 Poster: TAB-VCR: Tags and Attributes based Visual Commonsense Reasoning Baselines »
Jingxiang Lin · Unnat Jain · Alex Schwing -
2019 Poster: Convergent Policy Optimization for Safe Reinforcement Learning »
Ming Yu · Zhuoran Yang · Mladen Kolar · Zhaoran Wang -
2019 Poster: Implicit Regularization of Discrete Gradient Dynamics in Linear Neural Networks »
Gauthier Gidel · Francis Bach · Simon Lacoste-Julien -
2019 Poster: Painless Stochastic Gradient: Interpolation, Line-Search, and Convergence Rates »
Sharan Vaswani · Aaron Mishkin · Issam Laradji · Mark Schmidt · Gauthier Gidel · Simon Lacoste-Julien -
2019 Poster: Co-Generation with GANs using AIS based HMC »
Tiantian Fang · Alex Schwing -
2019 Poster: Sampled Softmax with Random Fourier Features »
Ankit Singh Rawat · Jiecao Chen · Felix Xinnan Yu · Ananda Theertha Suresh · Sanjiv Kumar -
2019 Poster: Invertible Convolutional Flow »
Mahdi Karami · Dale Schuurmans · Jascha Sohl-Dickstein · Laurent Dinh · Daniel Duckworth -
2019 Spotlight: Invertible Convolutional Flow »
Mahdi Karami · Dale Schuurmans · Jascha Sohl-Dickstein · Laurent Dinh · Daniel Duckworth -
2019 Poster: Efficient Deep Approximation of GMMs »
Shirin Jalali · Carl Nuzman · Iraj Saniee -
2019 Poster: Learning-Based Low-Rank Approximations »
Piotr Indyk · Ali Vakilian · Yang Yuan -
2019 Poster: Same-Cluster Querying for Overlapping Clusters »
Wasim Huleihel · Arya Mazumdar · Muriel Medard · Soumyabrata Pal -
2019 Poster: Space and Time Efficient Kernel Density Estimation in High Dimensions »
Arturs Backurs · Piotr Indyk · Tal Wagner -
2019 Poster: List-decodable Linear Regression »
Sushrut Karmalkar · Adam Klivans · Pravesh Kothari -
2019 Spotlight: List-decodable Linear Regression »
Sushrut Karmalkar · Adam Klivans · Pravesh Kothari -
2018 : Coffee break + posters 2 »
Jan Kremer · Erik McDermott · Brandon Carter · Albert Zeyer · Andreas Krug · Paul Pu Liang · Katherine Lee · Dominika Basaj · Abelino Jimenez · Lisa Fan · Gautam Bhattacharya · Tzeviya S Fuchs · David Gifford · Loren Lugosch · Orhan Firat · Benjamin Baer · JAHANGIR ALAM · Jamin Shin · Mirco Ravanelli · Paul Smolensky · Zining Zhu · Hamid Eghbal-zadeh · Skyler Seto · Imran Sheikh · Joao Felipe Santos · Yonatan Belinkov · Nadir Durrani · Oiwi Parker Jones · Shuai Tang · André Merboldt · Titouan Parcollet · Wei-Ning Hsu · Krishna Pillutla · Ehsan Hosseini-Asl · Monica Dinculescu · Alexander Amini · Ying Zhang · Taoli Cheng · Alain Tapp -
2018 : Mirco Ravanelli, "Interpretable convolutional filters with SincNet" »
Mirco Ravanelli -
2018 : Coffee break + posters 1 »
Samuel Myer · Wei-Ning Hsu · Jialu Li · Monica Dinculescu · Lea Schönherr · Ehsan Hosseini-Asl · Skyler Seto · Oiwi Parker Jones · Imran Sheikh · Thomas Manzini · Yonatan Belinkov · Nadir Durrani · Alexander Amini · Johanna Hansen · Gabi Shalev · Jamin Shin · Paul Smolensky · Lisa Fan · Zining Zhu · Hamid Eghbal-zadeh · Benjamin Baer · Abelino Jimenez · Joao Felipe Santos · Jan Kremer · Erik McDermott · Andreas Krug · Tzeviya S Fuchs · Shuai Tang · Brandon Carter · David Gifford · Albert Zeyer · André Merboldt · Krishna Pillutla · Katherine Lee · Titouan Parcollet · Orhan Firat · Gautam Bhattacharya · JAHANGIR ALAM · Mirco Ravanelli -
2018 : The effects of negative adaptation in Model-Agnostic Meta-Learning »
Tristan Deleu -
2018 : Workshop Opening »
Mirco Ravanelli · Dmitriy Serdyuk · Ehsan Variani · Bhuvana Ramabhadran -
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 Workshop: Interpretability and Robustness in Audio, Speech, and Language »
Mirco Ravanelli · Dmitriy Serdyuk · Ehsan Variani · Bhuvana Ramabhadran -
2018 Workshop: Privacy Preserving Machine Learning »
Adria Gascon · Aurélien Bellet · Niki Kilbertus · Olga Ohrimenko · Mariana Raykova · Adrian Weller -
2018 : Coffee Break and Poster Session I »
Pim de Haan · Bin Wang · Dequan Wang · Aadil Hayat · Ibrahim Sobh · Muhammad Asif Rana · Thibault Buhet · Nicholas Rhinehart · Arjun Sharma · Alex Bewley · Michael Kelly · Lionel Blondé · Ozgur S. Oguz · Vaibhav Viswanathan · Jeroen Vanbaar · Konrad Żołna · Negar Rostamzadeh · Rowan McAllister · Sanjay Thakur · Alexandros Kalousis · Chelsea Sidrane · Sujoy Paul · Daphne Chen · Michal Garmulewicz · Henryk Michalewski · Coline Devin · Hongyu Ren · Jiaming Song · Wen Sun · Hanzhang Hu · Wulong Liu · Emilie Wirbel -
2018 : Opening remarks »
Simon Lacoste-Julien · Gauthier Gidel -
2018 Workshop: Smooth Games Optimization and Machine Learning »
Simon Lacoste-Julien · Ioannis Mitliagkas · Gauthier Gidel · Vasilis Syrgkanis · Eva Tardos · Leon Bottou · Sebastian Nowozin -
2018 Poster: A convex program for bilinear inversion of sparse vectors »
Alireza Aghasi · Ali Ahmed · Paul Hand · Babhru Joshi -
2018 Poster: Contrastive Learning from Pairwise Measurements »
Yi Chen · Zhuoran Yang · Yuchen Xie · Zhaoran Wang -
2018 Poster: Overfitting or perfect fitting? Risk bounds for classification and regression rules that interpolate »
Mikhail Belkin · Daniel Hsu · Partha P Mitra -
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: Deep Structured Prediction with Nonlinear Output Transformations »
Colin Graber · Ofer Meshi · Alex Schwing -
2018 Poster: Provable Gaussian Embedding with One Observation »
Ming Yu · Zhuoran Yang · Tuo Zhao · Mladen Kolar · Zhaoran Wang -
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 Poster: Geometrically Coupled Monte Carlo Sampling »
Mark Rowland · Krzysztof Choromanski · François Chalus · Aldo Pacchiano · Tamas Sarlos · Richard Turner · Adrian Weller -
2018 Poster: Adversarially Robust Optimization with Gaussian Processes »
Ilija Bogunovic · Jonathan Scarlett · Stefanie Jegelka · Volkan Cevher -
2018 Poster: Multi-Agent Reinforcement Learning via Double Averaging Primal-Dual Optimization »
Hoi-To Wai · Zhuoran Yang · Zhaoran Wang · Mingyi Hong -
2018 Poster: Coupled Variational Bayes via Optimization Embedding »
Bo Dai · Hanjun Dai · Niao He · Weiyang Liu · Zhen Liu · Jianshu Chen · Lin Xiao · Le Song -
2018 Poster: Blind Deconvolutional Phase Retrieval via Convex Programming »
Ali Ahmed · Alireza Aghasi · Paul Hand -
2018 Spotlight: Geometrically Coupled Monte Carlo Sampling »
Mark Rowland · Krzysztof Choromanski · François Chalus · Aldo Pacchiano · Tamas Sarlos · Richard Turner · Adrian Weller -
2018 Spotlight: Adversarially Robust Optimization with Gaussian Processes »
Ilija Bogunovic · Jonathan Scarlett · Stefanie Jegelka · Volkan Cevher -
2018 Spotlight: Blind Deconvolutional Phase Retrieval via Convex Programming »
Ali Ahmed · Alireza Aghasi · Paul Hand -
2018 Poster: Quantifying Learning Guarantees for Convex but Inconsistent Surrogates »
Kirill Struminsky · Simon Lacoste-Julien · Anton Osokin -
2018 Poster: M-Walk: Learning to Walk over Graphs using Monte Carlo Tree Search »
Yelong Shen · Jianshu Chen · Po-Sen Huang · Yuqing Guo · Jianfeng Gao -
2018 Poster: Pipe-SGD: A Decentralized Pipelined SGD Framework for Distributed Deep Net Training »
Youjie Li · Mingchao Yu · Songze Li · Salman Avestimehr · Nam Sung Kim · Alex Schwing -
2018 Poster: PCA of high dimensional random walks with comparison to neural network training »
Joseph Antognini · Jascha Sohl-Dickstein -
2018 Poster: Out of the Box: Reasoning with Graph Convolution Nets for Factual Visual Question Answering »
Medhini Narasimhan · Svetlana Lazebnik · Alex Schwing -
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: GradiVeQ: Vector Quantization for Bandwidth-Efficient Gradient Aggregation in Distributed CNN Training »
Mingchao Yu · Zhifeng Lin · Krishna Narra · Songze Li · Youjie Li · Nam Sung Kim · Alex Schwing · Murali Annavaram · Salman Avestimehr -
2018 Poster: Phase Retrieval Under a Generative Prior »
Paul Hand · Oscar Leong · Vlad Voroninski -
2018 Oral: Phase Retrieval Under a Generative Prior »
Paul Hand · Oscar Leong · Vlad Voroninski -
2017 : Applications 2 »
Sam Greydanus -
2017 : A3T: Adversarially Augmented Adversarial Training »
Aristide Baratin · Simon Lacoste-Julien · Yoshua Bengio · Akram Erraqabi -
2017 : Invited talk: Challenges for Transparency »
Adrian Weller -
2017 : Data-dependent methods for similarity search in high dimensions »
Piotr Indyk -
2017 : On Structured Prediction Theory with Calibrated Convex Surrogate Losses. »
Simon Lacoste-Julien -
2017 : Closing remarks »
Adrian Weller -
2017 Symposium: Kinds of intelligence: types, tests and meeting the needs of society »
José Hernández-Orallo · Zoubin Ghahramani · Tomaso Poggio · Adrian Weller · Matthew Crosby -
2017 Poster: Breaking the Nonsmooth Barrier: A Scalable Parallel Method for Composite Optimization »
Fabian Pedregosa · Rémi Leblond · Simon Lacoste-Julien -
2017 Poster: From Parity to Preference-based Notions of Fairness in Classification »
Muhammad Bilal Zafar · Isabel Valera · Manuel Rodriguez · Krishna Gummadi · Adrian Weller -
2017 Poster: On Structured Prediction Theory with Calibrated Convex Surrogate Losses »
Anton Osokin · Francis Bach · Simon Lacoste-Julien -
2017 Poster: Online Convex Optimization with Stochastic Constraints »
Hao Yu · Michael Neely · Xiaohan Wei -
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: Dualing GANs »
Yujia Li · Alex Schwing · Kuan-Chieh Wang · Richard Zemel -
2017 Poster: Clustering with Noisy Queries »
Arya Mazumdar · Barna Saha -
2017 Poster: GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium »
Martin Heusel · Hubert Ramsauer · Thomas Unterthiner · Bernhard Nessler · Sepp Hochreiter -
2017 Spotlight: Breaking the Nonsmooth Barrier: A Scalable Parallel Method for Composite Optimization »
Fabian Pedregosa · Rémi Leblond · Simon Lacoste-Julien -
2017 Spotlight: Dualing GANs »
Yujia Li · Alex Schwing · Kuan-Chieh Wang · Richard Zemel -
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: On Structured Prediction Theory with Calibrated Convex Surrogate Losses »
Anton Osokin · Francis Bach · Simon Lacoste-Julien -
2017 Poster: The Unreasonable Effectiveness of Structured Random Orthogonal Embeddings »
Krzysztof Choromanski · Mark Rowland · Adrian Weller -
2017 Poster: MaskRNN: Instance Level Video Object Segmentation »
Yuan-Ting Hu · Jia-Bin Huang · Alex Schwing -
2017 Poster: Interpretable and Globally Optimal Prediction for Textual Grounding using Image Concepts »
Raymond A. Yeh · Jinjun Xiong · Wen-Mei Hwu · Minh Do · Alex Schwing -
2017 Poster: Practical Data-Dependent Metric Compression with Provable Guarantees »
Piotr Indyk · Ilya Razenshteyn · Tal Wagner -
2017 Poster: Estimation of the covariance structure of heavy-tailed distributions »
Xiaohan Wei · Stanislav Minsker -
2017 Poster: Eigen-Distortions of Hierarchical Representations »
Alexander Berardino · Valero Laparra · Johannes Ballé · Eero Simoncelli -
2017 Poster: Asynchronous Parallel Coordinate Minimization for MAP Inference »
Ofer Meshi · Alex Schwing -
2017 Poster: Collaborative Deep Learning in Fixed Topology Networks »
Zhanhong Jiang · Aditya Balu · Chinmay Hegde · Soumik Sarkar -
2017 Poster: Estimating High-dimensional Non-Gaussian Multiple Index Models via Stein’s Lemma »
Zhuoran Yang · Krishnakumar Balasubramanian · Zhaoran Wang · Han Liu -
2017 Poster: Semisupervised Clustering, AND-Queries and Locally Encodable Source Coding »
Arya Mazumdar · Soumyabrata Pal -
2017 Oral: Eigen-Distortions of Hierarchical Representations »
Alexander Berardino · Valero Laparra · Johannes Ballé · Eero Simoncelli -
2017 Oral: Interpretable and Globally Optimal Prediction for Textual Grounding using Image Concepts »
Raymond A. Yeh · Jinjun Xiong · Wen-Mei Hwu · Minh Do · Alex Schwing -
2017 Spotlight: Semisupervised Clustering, AND-Queries and Locally Encodable Source Coding »
Arya Mazumdar · Soumyabrata Pal -
2017 Poster: Uprooting and Rerooting Higher-Order Graphical Models »
Mark Rowland · Adrian Weller -
2017 Poster: High-Order Attention Models for Visual Question Answering »
Idan Schwartz · Alex Schwing · Tamir Hazan -
2017 Poster: On the Fine-Grained Complexity of Empirical Risk Minimization: Kernel Methods and Neural Networks »
Arturs Backurs · Piotr Indyk · Ludwig Schmidt -
2017 Poster: Query Complexity of Clustering with Side Information »
Arya Mazumdar · Barna Saha -
2017 Poster: Fast, Sample-Efficient Algorithms for Structured Phase Retrieval »
Gauri Jagatap · Chinmay Hegde -
2017 Poster: Diverse and Accurate Image Description Using a Variational Auto-Encoder with an Additive Gaussian Encoding Space »
Liwei Wang · Alex Schwing · Svetlana Lazebnik -
2017 Poster: SVCCA: Singular Vector Canonical Correlation Analysis for Deep Learning Dynamics and Interpretability »
Maithra Raghu · Justin Gilmer · Jason Yosinski · Jascha Sohl-Dickstein -
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 : Deep counter networks for asynchronous event-based processing »
Jonathan Binas -
2016 : Opening Remarks »
Jascha Sohl-Dickstein -
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 Workshop: Reliable Machine Learning in the Wild »
Dylan Hadfield-Menell · Adrian Weller · David Duvenaud · Jacob Steinhardt · Percy Liang -
2016 Symposium: Machine Learning and the Law »
Adrian Weller · Thomas D. Grant · Conrad McDonnell · Jatinder Singh -
2016 Poster: Fast recovery from a union of subspaces »
Chinmay Hegde · Piotr Indyk · Ludwig Schmidt -
2016 Poster: Constraints Based Convex Belief Propagation »
Yaniv Tenzer · Alex Schwing · Kevin Gimpel · Tamir Hazan -
2016 Poster: Exponential expressivity in deep neural networks through transient chaos »
Ben Poole · Subhaneil Lahiri · Maithra Raghu · Jascha Sohl-Dickstein · Surya Ganguli -
2016 Poster: Learning Deep Parsimonious Representations »
Renjie Liao · Alex Schwing · Richard Zemel · Raquel Urtasun -
2016 Poster: PAC-Bayesian Theory Meets Bayesian Inference »
Pascal Germain · Francis Bach · Alexandre Lacoste · Simon Lacoste-Julien -
2016 Poster: Equality of Opportunity in Supervised Learning »
Moritz Hardt · Eric Price · Eric Price · Nati Srebro -
2016 Poster: More Supervision, Less Computation: Statistical-Computational Tradeoffs in Weakly Supervised Learning »
Xinyang Yi · Zhaoran Wang · Zhuoran Yang · Constantine Caramanis · Han Liu -
2016 Poster: Mutual information for symmetric rank-one matrix estimation: A proof of the replica formula »
jean barbier · Mohamad Dia · Nicolas Macris · Florent Krzakala · Thibault Lesieur · Lenka Zdeborová -
2015 Workshop: Statistical Methods for Understanding Neural Systems »
Alyson Fletcher · Jakob H Macke · Ryan Adams · Jascha Sohl-Dickstein -
2015 Symposium: Algorithms Among Us: the Societal Impacts of Machine Learning »
Michael A Osborne · Adrian Weller · Murray Shanahan -
2015 Poster: On the Global Linear Convergence of Frank-Wolfe Optimization Variants »
Simon Lacoste-Julien · Martin Jaggi -
2015 Poster: Barrier Frank-Wolfe for Marginal Inference »
Rahul G Krishnan · Simon Lacoste-Julien · David Sontag -
2015 Poster: Practical and Optimal LSH for Angular Distance »
Alexandr Andoni · Piotr Indyk · Thijs Laarhoven · Ilya Razenshteyn · Ludwig Schmidt -
2015 Poster: Variance Reduced Stochastic Gradient Descent with Neighbors »
Thomas Hofmann · Aurelien Lucchi · Simon Lacoste-Julien · Brian McWilliams -
2015 Poster: Associative Memory via a Sparse Recovery Model »
Arya Mazumdar · Ankit Singh Rawat -
2015 Poster: Training Restricted Boltzmann Machine via the Thouless-Anderson-Palmer free energy »
Marylou Gabrie · Eric W Tramel · Florent Krzakala -
2015 Poster: Smooth and Strong: MAP Inference with Linear Convergence »
Ofer Meshi · Mehrdad Mahdavi · Alex Schwing -
2015 Poster: Deep Knowledge Tracing »
Chris Piech · Jonathan Bassen · Jonathan Huang · Surya Ganguli · Mehran Sahami · Leonidas Guibas · Jascha Sohl-Dickstein -
2015 Poster: Rethinking LDA: Moment Matching for Discrete ICA »
Anastasia Podosinnikova · Francis Bach · Simon Lacoste-Julien -
2015 Poster: Matrix Completion from Fewer Entries: Spectral Detectability and Rank Estimation »
Alaa Saade · Florent Krzakala · Lenka Zdeborová -
2014 Workshop: Optimal Transport and Machine Learning »
Marco Cuturi · Gabriel Peyré · Justin Solomon · Alexander Barvinok · Piotr Indyk · Robert McCann · Adam Oberman -
2014 Poster: Clamping Variables and Approximate Inference »
Adrian Weller · Tony Jebara -
2014 Poster: Efficient Inference of Continuous Markov Random Fields with Polynomial Potentials »
Shenlong Wang · Alex Schwing · Raquel Urtasun -
2014 Poster: Message Passing Inference for Large Scale Graphical Models with High Order Potentials »
Jian Zhang · Alex Schwing · Raquel Urtasun -
2014 Oral: Clamping Variables and Approximate Inference »
Adrian Weller · Tony Jebara -
2014 Poster: Spectral Clustering of graphs with the Bethe Hessian »
Alaa Saade · Florent Krzakala · Lenka Zdeborová -
2014 Poster: SAGA: A Fast Incremental Gradient Method With Support for Non-Strongly Convex Composite Objectives »
Aaron Defazio · Francis Bach · Simon Lacoste-Julien -
2013 Poster: Latent Structured Active Learning »
Wenjie Luo · Alex Schwing · Raquel Urtasun -
2012 Poster: Efficient and direct estimation of a neural subunit model for sensory coding »
Brett Vintch · Andrew Zaharia · J Movshon · Eero Simoncelli -
2012 Poster: Hierarchical spike coding of sound »
yan karklin · Chaitanya Ekanadham · Eero Simoncelli -
2012 Spotlight: Hierarchical spike coding of sound »
yan karklin · Chaitanya Ekanadham · Eero Simoncelli -
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: Globally Convergent Dual MAP LP Relaxation Solvers using Fenchel-Young Margins »
Alex Schwing · Tamir Hazan · Marc Pollefeys · Raquel Urtasun -
2011 Poster: Efficient coding with a population of Linear-Nonlinear neurons »
yan karklin · Eero Simoncelli -
2011 Poster: A blind sparse deconvolution method for neural spike identification »
Chaitanya Ekanadham · Daniel Tranchina · Eero Simoncelli -
2011 Spotlight: A blind sparse deconvolution method for neural spike identification »
Chaitanya Ekanadham · Daniel Tranchina · Eero Simoncelli -
2010 Poster: Implicit encoding of prior probabilities in optimal neural populations »
Deep Ganguli · Eero Simoncelli -
2009 Workshop: The Generative and Discriminative Learning Interface »
Simon Lacoste-Julien · Percy Liang · Guillaume Bouchard -
2009 Poster: Hierarchical Modeling of Local Image Features through $L_p$-Nested Symmetric Distributions »
Fabian H Sinz · Eero Simoncelli · Matthias Bethge -
2008 Oral: Reducing statistical dependencies in natural signals using radial Gaussianization »
Siwei Lyu · Eero Simoncelli -
2008 Poster: Reducing statistical dependencies in natural signals using radial Gaussianization »
Siwei Lyu · Eero Simoncelli -
2008 Poster: DiscLDA: Discriminative Learning for Dimensionality Reduction and Classification »
Simon Lacoste-Julien · Fei Sha · Michael Jordan -
2008 Tutorial: Statistical Models of Visual Images »
Eero Simoncelli -
2007 Poster: A Bayesian Model of Conditioned Perception »
Alan A Stocker · Eero Simoncelli -
2006 Poster: Statistical Modeling of Images with Fields of Gaussian Scale Mixtures »
Siwei Lyu · Eero Simoncelli -
2006 Poster: Learning to be Bayesian without Supervision »
Martin Raphan · Eero Simoncelli