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Author Information
Julius von Kügelgen (University of Cambridge and Max Planck Institute for Intelligent Systems)
I am a PhD student with Bernhard Schölkopf at the Max Planck Institute for Intelligent Systems in Tübingen. As part of the Cambridge-Tübingen programme I am also co-supervised by Adrian Weller at the University of Cambridge, where I spent the first year of my PhD. My research interests lie at the intersection of causal inference and machine learning. Previously, I studied Mathematics (BSc+MSci) at Imperial College London and Artificial Intelligence (MSc) at UPC Barcelona in Spain and at TU Delft in the Netherlands. I am originally from the beautiful Hamburg in northern Germany.
David Rohde (Criteo)
Candice Schumann (University of Maryland)
Grace Charles (Surgo Foundation)
Victor Veitch (Columbia University)
Vira Semenova (MIT)
Mert Demirer (MIT)
Vasilis Syrgkanis (Microsoft Research)
Suraj Nair (Stanford University)
Aahlad Puli (NYU)
Masatoshi Uehara (Harvard University)
Aditya Gopalan (Indian Institute of Science)
Yi Ding (University of Chicago)
Ignavier Ng (University of Toronto)
Khashayar Khosravi (Stanford University)
Eli Sherman (Johns Hopkins University)
Shuxi Zeng (Duke University)
I am a third year Ph.D. candidate in Statistical Science, Duke University. I obtained B.A. in Economics and B.S. in Mathematics from Tsinghua University, China. My research interest lies in the field of causal inference. I currently work on principal stratification, causal mechanism detection, applying deep learning techniques to causal analysis.
Aleksander Wieczorek (University of Basel)
Hao Liu (Caltech)
Kyra Gan (Carnegie Mellon University)
Jason Hartford (University of British Columbia)
Miruna Oprescu (Microsoft Research)
Alexander D'Amour (Google Brain)
Jörn Boehnke (UC Davis)
Yuta Saito (Tokyo Institute of Technology)
I am a fourth year undergraduate at Tokyo Institute of Technology. My research lies at the intersection of machine learning and causal inference called counterfactual machine learning. I am interested in the counterfactual nature of logged bandit feedback obtained from interactive systems, and ways of using biased real-world datasets to assist better decision making. Most recently, I have been focusing on the intersection of counterfactual machine learning and unsupervised domain adaptation.
Théophile Griveau-Billion (Imperial College London)
Chirag Modi (UC Berkeley)
Shyngys Karimov (University of Leuven)
Jeroen Berrevoets (Vrije Universiteit Brussel)
Logan Graham (University of Oxford)
Imke Mayer (CMAP / CNRS)
Dhanya Sridhar (Columbia University)
Issa Dahabreh (Brown)
Alan Mishler (CMU)
Duncan Wadsworth (Microsoft)
Khizar Qureshi (MIT)
Rahul Ladhania (University of Pennsylvania)
Gota Morishita (CyberAgent.Inc.)
I am Gota Morishita. I work for Cyberagent, inc. as researcher. My interest is causal machine learning, reinforcement learning and game theoretical multi agent learning.
Paul Welle (Civis Analytics)
More from the Same Authors
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2021 Spotlight: Counterfactual Invariance to Spurious Correlations in Text Classification »
Victor Veitch · Alexander D'Amour · Steve Yadlowsky · Jacob Eisenstein -
2021 : Open Bandit Dataset and Pipeline: Towards Realistic and Reproducible Off-Policy Evaluation »
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2021 : MESA: Offline Meta-RL for Safe Adaptation and Fault Tolerance »
Michael Luo · Ashwin Balakrishna · Brijen Thananjeyan · Suraj Nair · Julian Ibarz · Jie Tan · Chelsea Finn · Ion Stoica · Ken Goldberg -
2021 : Using Embeddings to Estimate Peer Influence on Social Networks »
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2021 : Mitigating Overlap Violations in Causal Inference with Text Data »
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2021 : Maintaining fairness across distribution shifts: do we have viable solutions for real-world applications? »
Jessica Schrouff · Natalie Harris · Sanmi Koyejo · Ibrahim Alabdulmohsin · Eva Schnider · Diana Mincu · Christina Chen · Awa Dieng · Yuan Liu · Vivek Natarajan · Katherine Heller · Alexander D'Amour -
2021 : Double/Debiased Machine Learning for Dynamic Treatment Effects via $g$-Estimation »
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2021 : Estimating the Long-Term Effects of Novel Treatments »
Keith Battocchi · Maggie Hei · Greg Lewis · Miruna Oprescu · Vasilis Syrgkanis -
2021 : Learning Invariant Representations with Missing Data »
Mark Goldstein · Adriel Saporta · Aahlad Puli · Rajesh Ranganath · Andrew Miller -
2021 : Using Embeddings to Estimate Peer Influence on Social Networks »
Irina Cristali · Victor Veitch -
2021 : Learned Benchmarks for Subseasonal Forecasting »
Soukayna Mouatadid · Paulo Orenstein · Genevieve Flaspohler · Miruna Oprescu · Judah Cohen · Franklyn Wang · Sean Knight · Maria Geogdzhayeva · Sam Levang · Ernest Fraenkel · Lester Mackey -
2022 : Active Bayesian Causal Inference »
Christian Toth · Lars Lorch · Christian Knoll · Andreas Krause · Franz Pernkopf · Robert Peharz · Julius von Kügelgen -
2022 : Evaluating vaccine allocation strategies using simulation-assisted causal modelling »
Armin Kekić · Jonas Dehning · Luigi Gresele · Julius von Kügelgen · Viola Priesemann · Bernhard Schölkopf -
2022 : Tailored Overlap for Learning Under Distribution Shift »
David Bruns-Smith · Alexander D'Amour · Avi Feller · Steve Yadlowsky -
2022 : Causal Estimation for Text Data with (Apparent) Overlap Violations »
Lin Gui · Victor Veitch -
2022 : Active Bayesian Causal inference »
Christian Toth · Lars Lorch · Christian Knoll · Andreas Krause · Franz Pernkopf · Robert Peharz · Julius von Kügelgen -
2023 Poster: Uncovering Meanings of Embeddings via Markov Boundaries »
Yibo Jiang · Bryon Aragam · Victor Veitch -
2023 Poster: Nonparametric Identifiability of Causal Representations from Unknown Interventions »
Julius von Kügelgen · Michel Besserve · Liang Wendong · Luigi Gresele · Armin Kekić · Elias Bareinboim · David Blei · Bernhard Schölkopf -
2023 Poster: Concept Algebra for Score-based Conditional Model »
Zihao Wang · Lin Gui · Jeffrey Negrea · Victor Veitch -
2023 Poster: Causal Component Analysis »
Liang Wendong · Armin Kekić · Julius von Kügelgen · Simon Buchholz · Michel Besserve · Luigi Gresele · Bernhard Schölkopf -
2023 Poster: Spuriosity Didn’t Kill the Classifier: Using Invariant Predictions to Harness Spurious Features »
Cian Eastwood · Shashank Singh · Andrei L Nicolicioiu · Marin Vlastelica Pogančić · Julius von Kügelgen · Bernhard Schölkopf -
2023 Poster: Using Causal Context to Select Algorithmic Fairness Metrics »
Jacy Anthis · Victor Veitch -
2023 Poster: Beyond Invariance: Test-Time Label-Shift Adaptation for Addressing ``Spurious'' Correlations »
Qingyao Sun · Kevin Murphy · Sayna Ebrahimi · Alexander D'Amour -
2022 Workshop: Deep Reinforcement Learning Workshop »
Karol Hausman · Qi Zhang · Matthew Taylor · Martha White · Suraj Nair · Manan Tomar · Risto Vuorio · Ted Xiao · Zeyu Zheng · Manan Tomar -
2022 Spotlight: Lightning Talks 1A-3 »
Kimia Noorbakhsh · Ronan Perry · Qi Lyu · Jiawei Jiang · Christian Toth · Olivier Jeunen · Xin Liu · Yuan Cheng · Lei Li · Manuel Rodriguez · Julius von Kügelgen · Lars Lorch · Nicolas Donati · Lukas Burkhalter · Xiao Fu · Zhongdao Wang · Songtao Feng · Ciarán Gilligan-Lee · Rishabh Mehrotra · Fangcheng Fu · Jing Yang · Bernhard Schölkopf · Ya-Li Li · Christian Knoll · Maks Ovsjanikov · Andreas Krause · Shengjin Wang · Hong Zhang · Mounia Lalmas · Bolin Ding · Bo Du · Yingbin Liang · Franz Pernkopf · Robert Peharz · Anwar Hithnawi · Julius von Kügelgen · Bo Li · Ce Zhang -
2022 Spotlight: Active Bayesian Causal Inference »
Christian Toth · Lars Lorch · Christian Knoll · Andreas Krause · Franz Pernkopf · Robert Peharz · Julius von Kügelgen -
2022 Spotlight: Causal Discovery in Heterogeneous Environments Under the Sparse Mechanism Shift Hypothesis »
Ronan Perry · Julius von Kügelgen · Bernhard Schölkopf -
2022 Spotlight: Embrace the Gap: VAEs Perform Independent Mechanism Analysis »
Patrik Reizinger · Luigi Gresele · Jack Brady · Julius von Kügelgen · Dominik Zietlow · Bernhard Schölkopf · Georg Martius · Wieland Brendel · Michel Besserve -
2022 Workshop: I Can’t Believe It’s Not Better: Understanding Deep Learning Through Empirical Falsification »
Arno Blaas · Sahra Ghalebikesabi · Javier Antorán · Fan Feng · Melanie F. Pradier · Ian Mason · David Rohde -
2022 Poster: Using Embeddings for Causal Estimation of Peer Influence in Social Networks »
Irina Cristali · Victor Veitch -
2022 Poster: Diagnosing failures of fairness transfer across distribution shift in real-world medical settings »
Jessica Schrouff · Natalie Harris · Sanmi Koyejo · Ibrahim Alabdulmohsin · Eva Schnider · Krista Opsahl-Ong · Alexander Brown · Subhrajit Roy · Diana Mincu · Christina Chen · Awa Dieng · Yuan Liu · Vivek Natarajan · Alan Karthikesalingam · Katherine Heller · Silvia Chiappa · Alexander D'Amour -
2022 Poster: Probable Domain Generalization via Quantile Risk Minimization »
Cian Eastwood · Alexander Robey · Shashank Singh · Julius von Kügelgen · Hamed Hassani · George J. Pappas · Bernhard Schölkopf -
2022 Poster: Causal Discovery in Heterogeneous Environments Under the Sparse Mechanism Shift Hypothesis »
Ronan Perry · Julius von Kügelgen · Bernhard Schölkopf -
2022 Poster: Invariant and Transportable Representations for Anti-Causal Domain Shifts »
Yibo Jiang · Victor Veitch -
2022 Poster: Embrace the Gap: VAEs Perform Independent Mechanism Analysis »
Patrik Reizinger · Luigi Gresele · Jack Brady · Julius von Kügelgen · Dominik Zietlow · Bernhard Schölkopf · Georg Martius · Wieland Brendel · Michel Besserve -
2022 Poster: Active Bayesian Causal Inference »
Christian Toth · Lars Lorch · Christian Knoll · Andreas Krause · Franz Pernkopf · Robert Peharz · Julius von Kügelgen -
2021 : Learned Benchmarks for Subseasonal Forecasting »
Soukayna Mouatadid · Paulo Orenstein · Genevieve Flaspohler · Miruna Oprescu · Judah Cohen · Franklyn Wang · Sean Knight · Maria Geogdzhayeva · Sam Levang · Ernest Fraenkel · Lester Mackey -
2021 : Julius von Kügelgen - Independent mechanism analysis, a new concept? »
Julius von Kügelgen -
2021 Poster: Double/Debiased Machine Learning for Dynamic Treatment Effects »
Greg Lewis · Vasilis Syrgkanis -
2021 Poster: Asymptotics of the Bootstrap via Stability with Applications to Inference with Model Selection »
Morgane Austern · Vasilis Syrgkanis -
2021 Poster: Estimating the Long-Term Effects of Novel Treatments »
Keith Battocchi · Eleanor Dillon · Maggie Hei · Greg Lewis · Miruna Oprescu · Vasilis Syrgkanis -
2021 Poster: Independent mechanism analysis, a new concept? »
Luigi Gresele · Julius von Kügelgen · Vincent Stimper · Bernhard Schölkopf · Michel Besserve -
2021 Poster: Greedy Approximation Algorithms for Active Sequential Hypothesis Testing »
Kyra Gan · Su Jia · Andrew Li -
2021 Poster: Inverse-Weighted Survival Games »
Xintian Han · Mark Goldstein · Aahlad Puli · Thomas Wies · Adler Perotte · Rajesh Ranganath -
2021 Poster: Reliable Causal Discovery with Improved Exact Search and Weaker Assumptions »
Ignavier Ng · Yujia Zheng · Jiji Zhang · Kun Zhang -
2021 Poster: Backward-Compatible Prediction Updates: A Probabilistic Approach »
Frederik Träuble · Julius von Kügelgen · Matthäus Kleindessner · Francesco Locatello · Bernhard Schölkopf · Peter Gehler -
2021 Poster: Self-Supervised Learning with Data Augmentations Provably Isolates Content from Style »
Julius von Kügelgen · Yash Sharma · Luigi Gresele · Wieland Brendel · Bernhard Schölkopf · Michel Besserve · Francesco Locatello -
2021 Poster: Counterfactual Invariance to Spurious Correlations in Text Classification »
Victor Veitch · Alexander D'Amour · Steve Yadlowsky · Jacob Eisenstein -
2020 : Contributed Talk 3: Fairness in Risk Assessment: Post-Processing to Achieve Counterfactual Equalized Odds »
Alan Mishler · Edward Kennedy · Alexandra Chouldechova -
2020 : Oral: Ignavier Ng »
Ignavier Ng -
2020 Poster: On the Role of Sparsity and DAG Constraints for Learning Linear DAGs »
Ignavier Ng · AmirEmad Ghassami · Kun Zhang -
2020 Poster: Exemplar Guided Active Learning »
Jason Hartford · Kevin Leyton-Brown · Hadas Raviv · Dan Padnos · Shahar Lev · Barak Lenz -
2020 Poster: General Control Functions for Causal Effect Estimation from IVs »
Aahlad Puli · Rajesh Ranganath -
2020 Poster: Sense and Sensitivity Analysis: Simple Post-Hoc Analysis of Bias Due to Unobserved Confounding »
Victor Veitch · Anisha Zaveri -
2020 Poster: Algorithmic recourse under imperfect causal knowledge: a probabilistic approach »
Amir-Hossein Karimi · Julius von Kügelgen · Bernhard Schölkopf · Isabel Valera -
2020 Poster: X-CAL: Explicit Calibration for Survival Analysis »
Mark Goldstein · Xintian Han · Aahlad Puli · Adler Perotte · Rajesh Ranganath -
2020 Poster: Causal Estimation with Functional Confounders »
Aahlad Puli · Adler Perotte · Rajesh Ranganath -
2020 Poster: A polynomial-time algorithm for learning nonparametric causal graphs »
Ming Gao · Yi Ding · Bryon Aragam -
2020 Poster: Minimax Estimation of Conditional Moment Models »
Nishanth Dikkala · Greg Lewis · Lester Mackey · Vasilis Syrgkanis -
2020 Spotlight: Algorithmic recourse under imperfect causal knowledge: a probabilistic approach »
Amir-Hossein Karimi · Julius von Kügelgen · Bernhard Schölkopf · Isabel Valera -
2020 Spotlight: Sense and Sensitivity Analysis: Simple Post-Hoc Analysis of Bias Due to Unobserved Confounding »
Victor Veitch · Anisha Zaveri -
2019 : Poster Spotlights »
Théophile Griveau-Billion · Rahul Singh · Zichen Zhang · Ciarán Lee · Jesse Krijthe · Grace Charles · Vira Semenova · Rahul Ladhania · Miruna Oprescu -
2019 : Contributed talk 2 »
Divyat Mahajan · Khashayar Khosravi · Alexander D'Amour -
2019 : Contributed talk 1 »
Daniel Chen · Jörn Boehnke · Yixin Wang · Jean Bonaldi -
2019 : Poster Session »
Matthia Sabatelli · Adam Stooke · Amir Abdi · Paulo Rauber · Leonard Adolphs · Ian Osband · Hardik Meisheri · Karol Kurach · Johannes Ackermann · Matt Benatan · GUO ZHANG · Chen Tessler · Dinghan Shen · Mikayel Samvelyan · Riashat Islam · Murtaza Dalal · Luke Harries · Andrey Kurenkov · Konrad Żołna · Sudeep Dasari · Kristian Hartikainen · Ofir Nachum · Kimin Lee · Markus Holzleitner · Vu Nguyen · Francis Song · Christopher Grimm · Felipe Leno da Silva · Yuping Luo · Yifan Wu · Alex Lee · Thomas Paine · Wei-Yang Qu · Daniel Graves · Yannis Flet-Berliac · Yunhao Tang · Suraj Nair · Matthew Hausknecht · Akhil Bagaria · Simon Schmitt · Bowen Baker · Paavo Parmas · Benjamin Eysenbach · Lisa Lee · Siyu Lin · Daniel Seita · Abhishek Gupta · Riley Simmons-Edler · Yijie Guo · Kevin Corder · Vikash Kumar · Scott Fujimoto · Adam Lerer · Ignasi Clavera Gilaberte · Nicholas Rhinehart · Ashvin Nair · Ge Yang · Lingxiao Wang · Sungryull Sohn · J. Fernando Hernandez-Garcia · Xian Yeow Lee · Rupesh Srivastava · Khimya Khetarpal · Chenjun Xiao · Luckeciano Carvalho Melo · Rishabh Agarwal · Tianhe Yu · Glen Berseth · Devendra Singh Chaplot · Jie Tang · Anirudh Srinivasan · Tharun Kumar Reddy Medini · Aaron Havens · Misha Laskin · Asier Mujika · Rohan Saphal · Joseph Marino · Alex Ray · Joshua Achiam · Ajay Mandlekar · Zhuang Liu · Danijar Hafner · Zhiwen Tang · Ted Xiao · Michael Walton · Jeff Druce · Ferran Alet · Zhang-Wei Hong · Stephanie Chan · Anusha Nagabandi · Hao Liu · Hao Sun · Ge Liu · Dinesh Jayaraman · John Co-Reyes · Sophia Sanborn -
2019 : Coffee break, posters, and 1-on-1 discussions »
Yangyi Lu · Daniel Chen · Hongseok Namkoong · Marie Charpignon · Maja Rudolph · Amanda Coston · Julius von Kügelgen · Niranjani Prasad · Paramveer Dhillon · Yunzong Xu · Yixin Wang · Alexander Markham · David Rohde · Rahul Singh · Zichen Zhang · Negar Hassanpour · Ankit Sharma · Ciarán Lee · Jean Pouget-Abadie · Jesse Krijthe · Divyat Mahajan · Nan Rosemary Ke · Peter Wirnsberger · Vira Semenova · Dmytro Mykhaylov · Dennis Shen · Kenta Takatsu · Liyang Sun · Jeremy Yang · Alexander Franks · Pak Kan Wong · Tauhid Zaman · Shira Mitchell · min kyoung kang · Qi Yang -
2019 : Poster Spotlights »
Hongseok Namkoong · Marie Charpignon · Maja Rudolph · Amanda Coston · Yuta Saito · Paramveer Dhillon · Alexander Markham -
2019 : Molecules and Genomes »
David Haussler · Djork-Arné Clevert · Michael Keiser · Alan Aspuru-Guzik · David Duvenaud · David Jones · Jennifer Wei · Alexander D'Amour -
2019 : Poster Session »
Ahana Ghosh · Javad Shafiee · Akhilan Boopathy · Alex Tamkin · Theodoros Vasiloudis · Vedant Nanda · Ali Baheri · Paul Fieguth · Andrew Bennett · Guanya Shi · Hao Liu · Arushi Jain · Jacob Tyo · Benjie Wang · Boxiao Chen · Carroll Wainwright · Chandramouli Shama Sastry · Chao Tang · Daniel S. Brown · David Inouye · David Venuto · Dhruv Ramani · Dimitrios Diochnos · Divyam Madaan · Dmitrii Krashenikov · Joel Oren · Doyup Lee · Eleanor Quint · elmira amirloo · Matteo Pirotta · Gavin Hartnett · Geoffroy Dubourg-Felonneau · Gokul Swamy · Pin-Yu Chen · Ilija Bogunovic · Jason Carter · Javier Garcia-Barcos · Jeet Mohapatra · Jesse Zhang · Jian Qian · John Martin · Oliver Richter · Federico Zaiter · Tsui-Wei Weng · Karthik Abinav Sankararaman · Kyriakos Polymenakos · Lan Hoang · mahdieh abbasi · Marco Gallieri · Mathieu Seurin · Matteo Papini · Matteo Turchetta · Matthew Sotoudeh · Mehrdad Hosseinzadeh · Nathan Fulton · Masatoshi Uehara · Niranjani Prasad · Oana-Maria Camburu · Patrik Kolaric · Philipp Renz · Prateek Jaiswal · Reazul Hasan Russel · Riashat Islam · Rishabh Agarwal · Alexander Aldrick · Sachin Vernekar · Sahin Lale · Sai Kiran Narayanaswami · Samuel Daulton · Sanjam Garg · Sebastian East · Shun Zhang · Soheil Dsidbari · Justin Goodwin · Victoria Krakovna · Wenhao Luo · Wesley Chung · Yuanyuan Shi · Yuh-Shyang Wang · Hongwei Jin · Ziping Xu -
2019 Poster: Making the Cut: A Bandit-based Approach to Tiered Interviewing »
Candice Schumann · Zhi Lang · Jeffrey Foster · John Dickerson -
2019 Poster: Semi-Parametric Efficient Policy Learning with Continuous Actions »
Victor Chernozhukov · Mert Demirer · Greg Lewis · Vasilis Syrgkanis -
2019 Poster: Low-Rank Bandit Methods for High-Dimensional Dynamic Pricing »
Jonas Mueller · Vasilis Syrgkanis · Matt Taddy -
2019 Poster: Intrinsically Efficient, Stable, and Bounded Off-Policy Evaluation for Reinforcement Learning »
Nathan Kallus · Masatoshi Uehara -
2019 Poster: Using Embeddings to Correct for Unobserved Confounding in Networks »
Victor Veitch · Yixin Wang · David Blei -
2019 Poster: Bayesian Optimization under Heavy-tailed Payoffs »
Sayak Ray Chowdhury · Aditya Gopalan -
2019 Spotlight: Bayesian Optimization under Heavy-tailed Payoffs »
Sayak Ray Chowdhury · Aditya Gopalan -
2019 Poster: Combinatorial Bandits with Relative Feedback »
Aadirupa Saha · Aditya Gopalan -
2019 Poster: Adapting Neural Networks for the Estimation of Treatment Effects »
Claudia Shi · David Blei · Victor Veitch -
2019 Poster: Machine Learning Estimation of Heterogeneous Treatment Effects with Instruments »
Vasilis Syrgkanis · Victor Lei · Miruna Oprescu · Maggie Hei · Keith Battocchi · Greg Lewis -
2019 Spotlight: Machine Learning Estimation of Heterogeneous Treatment Effects with Instruments »
Vasilis Syrgkanis · Victor Lei · Miruna Oprescu · Maggie Hei · Keith Battocchi · Greg Lewis -
2018 : Spotlights 2 »
Aditya Gopalan · Sungjoon Choi · Thomas Ringstrom · Roy Fox · Jonas Degrave · Xiya Cao · Karl Pertsch · Maximilian Igl · Brian Ichter -
2018 : Poster Session 1 »
Kyle H Ambert · Brandon Araki · Xiya Cao · Sungjoon Choi · Hao(Jackson) Cui · Jonas Degrave · Yaqi Duan · Mattie Fellows · Carlos Florensa · Karan Goel · Aditya Gopalan · Ming-Xu Huang · Jonathan Hunt · Cyril Ibrahim · Brian Ichter · Maximilian Igl · Zheng Tracy Ke · Igor Kiselev · Anuj Mahajan · Arash Mehrjou · Karl Pertsch · Alexandre Piche · Nicholas Rhinehart · Thomas Ringstrom · Reazul Hasan Russel · Oleh Rybkin · Ion Stoica · Sharad Vikram · Angelina Wang · Ting-Han Wei · Abigail H Wen · I-Chen Wu · Zhengwei Wu · Linhai Xie · Dinghan Shen -
2018 : A Bayesian Solution to the M-Bias Problem »
David Rohde -
2018 : Poster Session 1 + Coffee »
Tom Van de Wiele · Rui Zhao · J. Fernando Hernandez-Garcia · Fabio Pardo · Xian Yeow Lee · Xiaolin Andy Li · Marcin Andrychowicz · Jie Tang · Suraj Nair · Juhyeon Lee · Cédric Colas · S. M. Ali Eslami · Yen-Chen Wu · Stephen McAleer · Ryan Julian · Yang Xue · Matthia Sabatelli · Pranav Shyam · Alexandros Kalousis · Giovanni Montana · Emanuele Pesce · Felix Leibfried · Zhanpeng He · Chunxiao Liu · Yanjun Li · Yoshihide Sawada · Alexander Pashevich · Tejas Kulkarni · Keiran Paster · Luca Rigazio · Quan Vuong · Hyunggon Park · Minhae Kwon · Rivindu Weerasekera · Shamane Siriwardhanaa · Rui Wang · Ozsel Kilinc · Keith Ross · Yizhou Wang · Simon Schmitt · Thomas Anthony · Evan Cater · Forest Agostinelli · Tegg Sung · Shirou Maruyama · Alexander Shmakov · Devin Schwab · Mohammad Firouzi · Glen Berseth · Denis Osipychev · Jesse Farebrother · Jianlan Luo · William Agnew · Peter Vrancx · Jonathan Heek · Catalin Ionescu · Haiyan Yin · Megumi Miyashita · Nathan Jay · Noga H. Rotman · Sam Leroux · Shaileshh Bojja Venkatakrishnan · Henri Schmidt · Jack Terwilliger · Ishan Durugkar · Jonathan Sauder · David Kas · Arash Tavakoli · Alain-Sam Cohen · Philip Bontrager · Adam Lerer · Thomas Paine · Ahmed Khalifa · Ruben Rodriguez · Avi Singh · Yiming Zhang -
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: Removing Hidden Confounding by Experimental Grounding »
Nathan Kallus · Aahlad Puli · Uri Shalit -
2018 Spotlight: Removing Hidden Confounding by Experimental Grounding »
Nathan Kallus · Aahlad Puli · Uri Shalit -
2017 : Aligned AI Poster Session »
Amanda Askell · Rafal Muszynski · William Wang · Yaodong Yang · Quoc Nguyen · Bryan Kian Hsiang Low · Patrick Jaillet · Candice Schumann · Anqi Liu · Peter Eckersley · Angelina Wang · William Saunders -
2017 : Poster session »
Abbas Zaidi · Christoph Kurz · David Heckerman · YiJyun Lin · Stefan Riezler · Ilya Shpitser · Songbai Yan · Olivier Goudet · Yash Deshpande · Judea Pearl · Jovana Mitrovic · Brian Vegetabile · Tae Hwy Lee · Karen Sachs · Karthika Mohan · Reagan Rose · Julius Ramakers · Negar Hassanpour · Pierre Baldi · Razieh Nabi · Noah Hammarlund · Eli Sherman · Carolin Lawrence · Fattaneh Jabbari · Vira Semenova · Maria Dimakopoulou · Pratik Gajane · Russell Greiner · Ilias Zadik · Alexander Blocker · Hao Xu · Tal EL HAY · Tony Jebara · Benoit Rostykus -
2017 Workshop: Learning in the Presence of Strategic Behavior »
Nika Haghtalab · Yishay Mansour · Tim Roughgarden · Vasilis Syrgkanis · Jennifer Wortman Vaughan -
2017 Poster: Multiresolution Kernel Approximation for Gaussian Process Regression »
Yi Ding · Risi Kondor · Jonathan Eskreis-Winkler -
2017 Spotlight: Multiresolution Kernel Approximation for Gaussian Process Regression »
Yi Ding · Risi Kondor · Jonathan Eskreis-Winkler -
2017 Poster: Welfare Guarantees from Data »
Darrell Hoy · Denis Nekipelov · Vasilis Syrgkanis -
2017 Poster: Robust Optimization for Non-Convex Objectives »
Robert S Chen · Brendan Lucier · Yaron Singer · Vasilis Syrgkanis -
2017 Poster: A Sample Complexity Measure with Applications to Learning Optimal Auctions »
Vasilis Syrgkanis -
2017 Oral: Robust Optimization for Non-Convex Objectives »
Robert S Chen · Brendan Lucier · Yaron Singer · Vasilis Syrgkanis -
2016 Poster: Improved Regret Bounds for Oracle-Based Adversarial Contextual Bandits »
Vasilis Syrgkanis · Haipeng Luo · Akshay Krishnamurthy · Robert Schapire -
2016 Poster: Deep Learning for Predicting Human Strategic Behavior »
Jason Hartford · James R Wright · Kevin Leyton-Brown -
2016 Oral: Deep Learning for Predicting Human Strategic Behavior »
Jason Hartford · James R Wright · Kevin Leyton-Brown -
2015 : The general class of (sparse) random graphs arising from exchangeable point processes »
Victor Veitch -
2015 Poster: No-Regret Learning in Bayesian Games »
Jason Hartline · Vasilis Syrgkanis · Eva Tardos -
2015 Poster: Fast Convergence of Regularized Learning in Games »
Vasilis Syrgkanis · Alekh Agarwal · Haipeng Luo · Robert Schapire -
2015 Oral: Fast Convergence of Regularized Learning in Games »
Vasilis Syrgkanis · Alekh Agarwal · Haipeng Luo · Robert Schapire