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Author Information
Gergely Flamich (University of Cambridge)
Shashanka Ubaru (IBM T. J. Watson Research Center)
Charles Zheng (National Institute of Mental Health)
Josip Djolonga (Google Research, Brain Team)
Kristoffer Wickstrøm (UiT The Arctic University of Norway)
Diego Granziol (University of Oxford)
Konstantinos Pitas (EPFL)
Jun Li (Florida International University)
Robert Williamson (Australian National University & Data61)
Sangwoong Yoon (Seoul National University)
Kwot Sin Lee (University of Cambridge)
Julian Zilly (ETH Zurich)
PhD student at ETH Zurich
Linda Petrini (Google)
Ian Fischer (Google)
Zhe Dong (Google AI)
Alexander Alemi (Google)
Bao-Ngoc Nguyen (Singapore University of Technology and Design)
Rob Brekelmans (University of Southern California)
Tailin Wu (MIT)
Aditya Mahajan (McGill University)
Alexander Li (University of California, Berkeley)
Kirankumar Shiragur (Stanford University)
Yair Carmon (Stanford University)
Linara Adilova (Fraunhofer IAIS)
SHIYU LIU (National University of Singapore)
Bang An (State University of New York at Buffalo)
Sanjeeb Dash (IBM Research)
Oktay Gunluk (IBM Research)
Arya Mazumdar (University of Massachusetts Amherst)
Mehul Motani (National University of Singapore)
Mehul Motani received the B.E. degree from Cooper Union, New York, NY, the M.S. degree from Syracuse University, Syracuse, NY, and the Ph.D. degree from Cornell University, Ithaca, NY, all in Electrical and Computer Engineering. Dr. Motani is currently an Associate Professor in the Electrical and Computer Engineering Department at the National University of Singapore (NUS) and a Visiting Research Collaborator at Princeton University. Previously, he was a Visiting Fellow at Princeton University. He was also a Research Scientist at the Institute for Infocomm Research in Singapore, for three years, and a Systems Engineer at Lockheed Martin in Syracuse, NY for over four years. His research interests include information theory, machine learning, wireless and sensor networks, and energy harvesting communications. Dr. Motani was the recipient of the Intel Foundation Fellowship for his Ph.D. research, the NUS Annual Teaching Excellence Award, the NUS Faculty of Engineering Innovative Teaching Award, and the NUS Faculty of Engineering Teaching Honours List Award. He actively participates in the Institute of Electrical and Electronics Engineers (IEEE) and the Association for Computing Machinery (ACM). He is a Fellow of the IEEE and has served as the Secretary of the IEEE Information Theory Society Board of Governors. He has served as an Associate Editor for both the IEEE Transactions on Information Theory and the IEEE Transactions on Communications. He has also served on the Organizing and Technical Program Committees of numerous IEEE and ACM conferences.
Julia Rosenzweig (Fraunhofer IAIS)
Michael Kamp (Fraunhofer IAIS)
Marton Havasi (University of Cambridge)
Leighton P Barnes (Stanford University)
Zhengqing Zhou (Stanford University)
Yi Hao (University of California, San Diego)
Fifth-year Ph.D. student supervised by Prof. Alon Orlitsky at UC San Diego. Broadly interested in Machine Learning, Learning Theory, Algorithm Design, Symbolic and Numerical Optimization. Seeking a summer 2020 internship in Data Science and Machine Learning.
Dylan Foster (MIT)
Yuval Benjamini (Hebrew University)
Nati Srebro (TTI-Chicago)
Michael Tschannen (Google Brain)
Paul Rubenstein (Cambridge / Max Planck Institute IS)
Sylvain Gelly (Google Brain)
John Duchi (Stanford)
Aaron Sidford (Stanford)
Robin Ru (Oxford University)
Stefan Zohren (Oxford University)
Murtaza Dalal (University of California, Berkeley)
Michael A Osborne (U Oxford)
Stephen J Roberts (University of Oxford)
Moses Charikar (Stanford University)
Jayakumar Subramanian (McGill University)
Xiaodi Fan (Florida International University)
Max Schwarzer (Mila, Université de Montréal)
Nicholas Roberts (Carnegie Mellon University)
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.
Vinay Prabhu (UnifyID Inc)
Aram Galstyan (USC Information Sciences Institute)
Greg Ver Steeg (USC Information Sciences Institute)
Lalitha Sankar (Arizona State University)
Yung-Kyun Noh (Seoul National University)
Gautam Dasarathy (Arizona State University)
Frank Park (Seoul National University)
Ngai-Man (Man) Cheung (Singapore University of Technology and Design)
Ngoc-Trung Tran (Singapore University of Technology and Design)
Linxiao Yang (University of Electronic Science and Technology of China; Singapore University of Technology and Design)
Ben Poole (Google Brain)
Andrea Censi (ETH Zurich)
Tristan Sylvain (MILA)
R Devon Hjelm (Microsoft Research)
Bangjie Liu (Citadel)
Jose Gallego-Posada (Mila, Université de Montréal)
Tyler Sypherd (Arizona State University)
Kai Yang (Tongji University)
Jan Nikolas Morshuis (SAP ML Research)
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Blake Woodworth · Kumar Kshitij Patel · Nati Srebro -
2020 Poster: Minibatch Stochastic Approximate Proximal Point Methods »
Hilal Asi · Karan Chadha · Gary Cheng · John Duchi -
2020 Spotlight: Differentiable Causal Discovery from Interventional Data »
Philippe Brouillard · Sébastien Lachapelle · Alexandre Lacoste · Simon Lacoste-Julien · Alexandre Drouin -
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: Minibatch Stochastic Approximate Proximal Point Methods »
Hilal Asi · Karan Chadha · Gary Cheng · John Duchi -
2020 Spotlight: DisARM: An Antithetic Gradient Estimator for Binary Latent Variables »
Zhe Dong · Andriy Mnih · George Tucker -
2020 Oral: Acceleration with a Ball Optimization Oracle »
Yair Carmon · Arun Jambulapati · Qijia Jiang · Yujia Jin · Yin Tat Lee · Aaron Sidford · Kevin Tian -
2020 Oral: High-Fidelity Generative Image Compression »
Fabian Mentzer · George D Toderici · Michael Tschannen · Eirikur Agustsson -
2020 Poster: Generalized Hindsight for Reinforcement Learning »
Alexander Li · Lerrel Pinto · Pieter Abbeel -
2020 Poster: Profile Entropy: A Fundamental Measure for the Learnability and Compressibility of Distributions »
Yi Hao · Alon Orlitsky -
2020 Poster: Deep Reinforcement and InfoMax Learning »
Bogdan Mazoure · Remi Tachet des Combes · Thang Long Doan · Philip Bachman · R Devon Hjelm -
2020 Poster: Provably Efficient Online Hyperparameter Optimization with Population-Based Bandits »
Jack Parker-Holder · Vu Nguyen · Stephen J Roberts -
2020 Poster: Learning the Linear Quadratic Regulator from Nonlinear Observations »
Zakaria Mhammedi · Dylan Foster · Max Simchowitz · Dipendra Misra · Wen Sun · Akshay Krishnamurthy · Alexander Rakhlin · John Langford -
2020 Poster: Instance-optimality in differential privacy via approximate inverse sensitivity mechanisms »
Hilal Asi · John Duchi -
2020 Session: Orals & Spotlights Track 11: Learning Theory »
Dylan Foster · Nicolò Cesa-Bianchi -
2020 Poster: Independent Policy Gradient Methods for Competitive Reinforcement Learning »
Constantinos Daskalakis · Dylan Foster · Noah Golowich -
2020 : Real World RL with Vowpal Wabbit: Beyond Contextual Bandits »
John Langford · Marek Wydmuch · Maryam Majzoubi · Adith Swaminathan · · Dylan Foster · Paul Mineiro -
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 : 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 : Fair Universal Representations via Generative Models and Model Auditing Guarantees »
Lalitha Sankar -
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 : 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 : 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 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: 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 : 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 »
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 : Invited Talk: Alexander A Alemi »
Alexander Alemi -
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 : Poster session »
Michael Melese Woldeyohannis · Bernardt Duvenhage · Nyamos Waigama · Asaye Bir Senay · Claire Babirye · Tensaye Ayalew · Kelechi Ogueji · Vinay Prabhu · Prabu Ravindran · Fadilulah Wahab · ChukwuNonso H Nwokoye · Paul Duckworth · Hafte Abera · Abebe Mideksa · Loubna Benabbou · Anugraha Sinha · Ivan Kiskin · Robert Soden · Tupokigwe Isagah · Rehema Mwawado · Yimer Mohammed · Bryan Wilder · Daniel Omeiza · Sunayana Rane · Richard Mgaya · Samsun Knight · Jessenia Gonzalez Villarreal · Eyob Beyene · Monika Obrocka Tulinska · Luis Fernando Cantu Diaz de Leon · Joseph Aro · Michael T Smith · Michael Famoroti · Praneeth Vepakomma · Ramesh Raskar · Debjani Bhowmick · Chukwunonso H Nwokoye · Alejandro Noriega Campero · Hope Mbelwa · Anusua Trivedi -
2019 : Poster Session »
Eduard Gorbunov · Alexandre d'Aspremont · Lingxiao Wang · Liwei Wang · Boris Ginsburg · Alessio Quaglino · Camille Castera · Saurabh Adya · Diego Granziol · Rudrajit Das · Raghu Bollapragada · Fabian Pedregosa · Martin Takac · Majid Jahani · Sai Praneeth Karimireddy · Hilal Asi · Balint Daroczy · Leonard Adolphs · Aditya Rawal · Nicolas Brandt · Minhan Li · Giuseppe Ughi · Orlando Romero · Ivan Skorokhodov · Damien Scieur · Kiwook Bae · Konstantin Mishchenko · Rohan Anil · Vatsal Sharan · Aditya Balu · Chao Chen · Zhewei Yao · Tolga Ergen · Paul Grigas · Chris Junchi Li · Jimmy Ba · Stephen J Roberts · Sharan Vaswani · Armin Eftekhari · Chhavi Sharma -
2019 : Poster session »
Sebastian Farquhar · Erik Daxberger · Andreas Look · Matt Benatan · Ruiyi Zhang · Marton Havasi · Fredrik Gustafsson · James A Brofos · Nabeel Seedat · Micha Livne · Ivan Ustyuzhaninov · Adam Cobb · Felix D McGregor · Patrick McClure · Tim R. Davidson · Gaurush Hiranandani · Sanjeev Arora · Masha Itkina · Didrik Nielsen · William Harvey · Matias Valdenegro-Toro · Stefano Peluchetti · Riccardo Moriconi · Tianyu Cui · Vaclav Smidl · Taylan Cemgil · Jack Fitzsimons · He Zhao · · mariana vargas vieyra · Apratim Bhattacharyya · Rahul Sharma · Geoffroy Dubourg-Felonneau · Jonathan Warrell · Slava Voloshynovskiy · Mihaela Rosca · Jiaming Song · Andrew Ross · Homa Fashandi · Ruiqi Gao · Hooshmand Shokri Razaghi · Joshua Chang · Zhenzhong Xiao · Vanessa Boehm · Giorgio Giannone · Ranganath Krishnan · Joe Davison · Arsenii Ashukha · Jeremiah Liu · Sicong (Sheldon) Huang · Evgenii Nikishin · Sunho Park · Nilesh Ahuja · Mahesh Subedar · · Artyom Gadetsky · Jhosimar Arias Figueroa · Tim G. J. Rudner · Waseem Aslam · Adrián Csiszárik · John Moberg · Ali Hebbal · Kathrin Grosse · Pekka Marttinen · Bang An · Hlynur Jónsson · Samuel Kessler · Abhishek Kumar · Mikhail Figurnov · Omesh Tickoo · Steindor Saemundsson · Ari Heljakka · Dániel Varga · Niklas Heim · Simone Rossi · Max Laves · Waseem Gharbieh · Nicholas Roberts · Luis Armando Pérez Rey · Matthew Willetts · Prithvijit Chakrabarty · Sumedh Ghaisas · Carl Shneider · Wray Buntine · Kamil Adamczewski · Xavier Gitiaux · Suwen Lin · Hao Fu · Gunnar Rätsch · Aidan Gomez · Erik Bodin · Dinh Phung · Lennart Svensson · Juliano Tusi Amaral Laganá Pinto · Milad Alizadeh · Jianzhun Du · Kevin Murphy · Beatrix Benkő · Shashaank Vattikuti · Jonathan Gordon · Christopher Kanan · Sontje Ihler · Darin Graham · Michael Teng · Louis Kirsch · Tomas Pevny · Taras Holotyak -
2019 : Spotlight talks »
Diego Granziol · Fabian Pedregosa · Hilal Asi -
2019 Workshop: Information Theory and Machine Learning »
Shengjia Zhao · Jiaming Song · Yanjun Han · Kristy Choi · Pratyusha Kalluri · Ben Poole · Alex Dimakis · Jiantao Jiao · Tsachy Weissman · Stefano Ermon -
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: Unified Sample-Optimal Property Estimation in Near-Linear Time »
Yi Hao · Alon Orlitsky -
2019 Poster: A General Framework for Symmetric Property Estimation »
Moses Charikar · Kirankumar Shiragur · Aaron Sidford -
2019 Poster: Learning Representations by Maximizing Mutual Information Across Views »
Philip Bachman · R Devon Hjelm · William Buchwalter -
2019 Poster: Variance Reduction for Matrix Games »
Yair Carmon · Yujia Jin · Aaron Sidford · Kevin Tian -
2019 Poster: Reducing Noise in GAN Training with Variance Reduced Extragradient »
Tatjana Chavdarova · Gauthier Gidel · François Fleuret · Simon Lacoste-Julien -
2019 Poster: Unsupervised State Representation Learning in Atari »
Ankesh Anand · Evan Racah · Sherjil Ozair · Yoshua Bengio · Marc-Alexandre Côté · R Devon Hjelm -
2019 Poster: Self-supervised GAN: Analysis and Improvement with Multi-class Minimax Game »
Ngoc-Trung Tran · Viet-Hung Tran · Bao-Ngoc Nguyen · Linxiao Yang · Ngai-Man (Man) Cheung -
2019 Oral: Variance Reduction for Matrix Games »
Yair Carmon · Yujia Jin · Aaron Sidford · Kevin Tian -
2019 Poster: Batched Multi-armed Bandits Problem »
Zijun Gao · Yanjun Han · Zhimei Ren · Zhengqing Zhou -
2019 Poster: The Broad Optimality of Profile Maximum Likelihood »
Yi Hao · Alon Orlitsky -
2019 Poster: Model Selection for Contextual Bandits »
Dylan Foster · Akshay Krishnamurthy · Haipeng Luo -
2019 Spotlight: The Broad Optimality of Profile Maximum Likelihood »
Yi Hao · Alon Orlitsky -
2019 Spotlight: Model Selection for Contextual Bandits »
Dylan Foster · Akshay Krishnamurthy · Haipeng Luo -
2019 Oral: Batched Multi-armed Bandits Problem »
Zijun Gao · Yanjun Han · Zhimei Ren · Zhengqing Zhou -
2019 Poster: Unlabeled Data Improves Adversarial Robustness »
Yair Carmon · Aditi Raghunathan · Ludwig Schmidt · John Duchi · Percy Liang -
2019 Poster: Discrete Flows: Invertible Generative Models of Discrete Data »
Dustin Tran · Keyon Vafa · Kumar Agrawal · Laurent Dinh · Ben Poole -
2019 Poster: Principal Component Projection and Regression in Nearly Linear Time through Asymmetric SVRG »
Yujia Jin · Aaron Sidford -
2019 Poster: Fast structure learning with modular regularization »
Greg Ver Steeg · Hrayr Harutyunyan · Daniel Moyer · Aram Galstyan -
2019 Spotlight: Principal Component Projection and Regression in Nearly Linear Time through Asymmetric SVRG »
Yujia Jin · Aaron Sidford -
2019 Spotlight: Fast structure learning with modular regularization »
Greg Ver Steeg · Hrayr Harutyunyan · Daniel Moyer · Aram Galstyan -
2019 Poster: Necessary and Sufficient Geometries for Gradient Methods »
Daniel Levy · John Duchi -
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: On Adversarial Mixup Resynthesis »
Christopher Beckham · Sina Honari · Alex Lamb · Vikas Verma · Farnoosh Ghadiri · R Devon Hjelm · Yoshua Bengio · Chris Pal -
2019 Poster: Hypothesis Set Stability and Generalization »
Dylan Foster · Spencer Greenberg · Satyen Kale · Haipeng Luo · Mehryar Mohri · Karthik Sridharan -
2019 Poster: Multivariate Distributionally Robust Convex Regression under Absolute Error Loss »
Jose Blanchet · Peter W Glynn · Jun Yan · Zhengqing Zhou -
2019 Poster: Complexity of Highly Parallel Non-Smooth Convex Optimization »
Sebastien Bubeck · Qijia Jiang · Yin-Tat Lee · Yuanzhi Li · Aaron Sidford -
2019 Oral: Necessary and Sufficient Geometries for Gradient Methods »
Daniel Levy · John Duchi -
2019 Spotlight: Complexity of Highly Parallel Non-Smooth Convex Optimization »
Sebastien Bubeck · Qijia Jiang · Yin-Tat Lee · Yuanzhi Li · Aaron Sidford -
2019 Poster: A Primal-Dual link between GANs and Autoencoders »
Hisham Husain · Richard Nock · Robert Williamson -
2019 Poster: Exact Rate-Distortion in Autoencoders via Echo Noise »
Rob Brekelmans · Daniel Moyer · Aram Galstyan · Greg Ver Steeg -
2019 Poster: Practical and Consistent Estimation of f-Divergences »
Paul Rubenstein · Olivier Bousquet · Josip Djolonga · Carlos Riquelme · Ilya Tolstikhin -
2019 Poster: Same-Cluster Querying for Overlapping Clusters »
Wasim Huleihel · Arya Mazumdar · Muriel Medard · Soumyabrata Pal -
2019 Poster: A Direct tilde{O}(1/epsilon) Iteration Parallel Algorithm for Optimal Transport »
Arun Jambulapati · Aaron Sidford · Kevin Tian -
2018 : Live competition The AI Driving Olympics: nuTonomy sponsor placeholder »
Andrea Censi -
2018 : Live competition The AI Driving Olympics: Supervised Learning approaches »
Manfred Díaz · Julian Zilly -
2018 : Poster Session I »
Aniruddh Raghu · Daniel Jarrett · Kathleen Lewis · Elias Chaibub Neto · Nicholas Mastronarde · Shazia Akbar · Chun-Hung Chao · Henghui Zhu · Seth Stafford · Luna Zhang · Jen-Tang Lu · Changhee Lee · Adityanarayanan Radhakrishnan · Fabian Falck · Liyue Shen · Daniel Neil · Yusuf Roohani · Aparna Balagopalan · Brett Marinelli · Hagai Rossman · Sven Giesselbach · Jose Javier Gonzalez Ortiz · Edward De Brouwer · Byung-Hoon Kim · Rafid Mahmood · Tzu Ming Hsu · Antonio Ribeiro · Rumi Chunara · Agni Orfanoudaki · Kristen Severson · Mingjie Mai · Sonali Parbhoo · Albert Haque · Viraj Prabhu · Di Jin · Alena Harley · Geoffroy Dubourg-Felonneau · Xiaodan Hu · Maithra Raghu · Jonathan Warrell · Nelson Johansen · Wenyuan Li · Marko Järvenpää · Satya Narayan Shukla · Sarah Tan · Vincent Fortuin · Beau Norgeot · Yi-Te Hsu · Joel H Saltz · Veronica Tozzo · Andrew Miller · Guillaume Ausset · Azin Asgarian · Francesco Paolo Casale · Antoine Neuraz · Bhanu Pratap Singh Rawat · Turgay Ayer · Xinyu Li · Mehul Motani · Nathaniel Braman · Laetitia M Shao · Adrian Dalca · Hyunkwang Lee · Emma Pierson · Sandesh Ghimire · Yuji Kawai · Owen Lahav · Anna Goldenberg · Denny Wu · Pavitra Krishnaswamy · Colin Pawlowski · Arijit Ukil · Yuhui Zhang -
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 : Posters and Open Discussions (see below for poster titles) »
Ramya Malur Srinivasan · Miguel Perez · Yuanyuan Liu · Ben Wood · Dan Philps · Kyle Brown · Daniel Martin · Mykola Pechenizkiy · Luca Costabello · Rongguang Wang · Suproteem Sarkar · Sangwoong Yoon · Zhuoran Xiong · Enguerrand Horel · Zhu (Drew) Zhang · Ulf Johansson · Jonathan Kochems · Gregory Sidier · Prashant Reddy · Lana Cuthbertson · Yvonne Wambui · Christelle Marfaing · Galen Harrison · Irene Unceta Mendieta · Thomas Kehler · Mark Weber · Li Ling · Ceena Modarres · Abhinav Dhall · Arash Nourian · David Byrd · Ajay Chander · Xiao-Yang Liu · Hongyang Yang · Shuang (Sophie) Zhai · Freddy Lecue · Sirui Yao · Rory McGrath · Artur Garcez · Vangelis Bacoyannis · Alexandre Garcia · Lukas Gonon · Mark Ibrahim · Melissa Louie · Omid Ardakanian · Cecilia Sönströd · Kojin Oshiba · Chaofan Chen · Suchen Jin · aldo pareja · Toyo Suzumura -
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 : Spotlight talks (session 3) »
Farzaneh Mahdisoltani · Frederik Kratzert · SUBBAREDDY OOTA · Mehul Motani · Tryambak Gangopadhyay · Sathwik Tejaswi Madhusudhan · Marc Rußwurm · Mahta Mousavi · Mihir Jain -
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: Exploiting Numerical Sparsity for Efficient Learning : Faster Eigenvector Computation and Regression »
Neha Gupta · Aaron Sidford -
2018 Poster: Graph Oracle Models, Lower Bounds, and Gaps for Parallel Stochastic Optimization »
Blake Woodworth · Jialei Wang · Adam Smith · Brendan McMahan · Nati Srebro -
2018 Poster: Invariant Representations without Adversarial Training »
Daniel Moyer · Shuyang Gao · Rob Brekelmans · Aram Galstyan · Greg Ver Steeg -
2018 Poster: Watch Your Step: Learning Node Embeddings via Graph Attention »
Sami Abu-El-Haija · Bryan Perozzi · Rami Al-Rfou · Alexander Alemi -
2018 Spotlight: Graph Oracle Models, Lower Bounds, and Gaps for Parallel Stochastic Optimization »
Blake Woodworth · Jialei Wang · Adam Smith · Brendan McMahan · Nati Srebro -
2018 Poster: Contextual bandits with surrogate losses: Margin bounds and efficient algorithms »
Dylan Foster · Akshay Krishnamurthy -
2018 Poster: Provable Variational Inference for Constrained Log-Submodular Models »
Josip Djolonga · Stefanie Jegelka · Andreas Krause -
2018 Poster: Boolean Decision Rules via Column Generation »
Sanjeeb Dash · Oktay Gunluk · Dennis Wei -
2018 Poster: Deep Generative Models for Distribution-Preserving Lossy Compression »
Michael Tschannen · Eirikur Agustsson · Mario Lucic -
2018 Poster: Inference in Deep Gaussian Processes using Stochastic Gradient Hamiltonian Monte Carlo »
Marton Havasi · José Miguel Hernández-Lobato · Juan J. Murillo-Fuentes -
2018 Poster: Implicit Bias of Gradient Descent on Linear Convolutional Networks »
Suriya Gunasekar · Jason Lee · Daniel Soudry · Nati Srebro -
2018 Spotlight: Boolean Decision Rules via Column Generation »
Sanjeeb Dash · Oktay Gunluk · Dennis Wei -
2018 Poster: On Learning Markov Chains »
Yi Hao · Alon Orlitsky · Venkatadheeraj Pichapati -
2018 Poster: The Everlasting Database: Statistical Validity at a Fair Price »
Blake Woodworth · Vitaly Feldman · Saharon Rosset · Nati Srebro -
2018 Poster: GILBO: One Metric to Measure Them All »
Alexander Alemi · Ian Fischer -
2018 Poster: Visual Reinforcement Learning with Imagined Goals »
Ashvin Nair · Vitchyr Pong · Murtaza Dalal · Shikhar Bahl · Steven Lin · Sergey Levine -
2018 Poster: Analysis of Krylov Subspace Solutions of Regularized Non-Convex Quadratic Problems »
Yair Carmon · John Duchi -
2018 Oral: Analysis of Krylov Subspace Solutions of Regularized Non-Convex Quadratic Problems »
Yair Carmon · John Duchi -
2018 Spotlight: Visual Reinforcement Learning with Imagined Goals »
Ashvin Nair · Vitchyr Pong · Murtaza Dalal · Shikhar Bahl · Steven Lin · Sergey Levine -
2018 Spotlight: GILBO: One Metric to Measure Them All »
Alexander Alemi · Ian Fischer -
2018 Poster: Quantifying Learning Guarantees for Convex but Inconsistent Surrogates »
Kirill Struminsky · Simon Lacoste-Julien · Anton Osokin -
2018 Poster: A loss framework for calibrated anomaly detection »
Aditya Menon · Robert Williamson -
2018 Poster: Near-Optimal Time and Sample Complexities for Solving Markov Decision Processes with a Generative Model »
Aaron Sidford · Mengdi Wang · Xian Wu · Lin Yang · Yinyu Ye -
2018 Poster: Generalizing to Unseen Domains via Adversarial Data Augmentation »
Riccardo Volpi · Hongseok Namkoong · Ozan Sener · John Duchi · Vittorio Murino · Silvio Savarese -
2018 Poster: Constant Regret, Generalized Mixability, and Mirror Descent »
Zakaria Mhammedi · Robert Williamson -
2018 Poster: On preserving non-discrimination when combining expert advice »
Avrim Blum · Suriya Gunasekar · Thodoris Lykouris · Nati Srebro -
2018 Poster: Uniform Convergence of Gradients for Non-Convex Learning and Optimization »
Dylan Foster · Ayush Sekhari · Karthik Sridharan -
2018 Poster: Data Amplification: A Unified and Competitive Approach to Property Estimation »
Yi Hao · Alon Orlitsky · Ananda Theertha Suresh · Yihong Wu -
2018 Spotlight: Constant Regret, Generalized Mixability, and Mirror Descent »
Zakaria Mhammedi · Robert Williamson -
2018 Spotlight: A loss framework for calibrated anomaly detection »
Aditya Menon · Robert Williamson -
2018 Poster: Scalable End-to-End Autonomous Vehicle Testing via Rare-event Simulation »
Matthew O'Kelly · Aman Sinha · Hongseok Namkoong · Russ Tedrake · John Duchi -
2017 : Fast Information-theoretic Bayesian Optimisation »
Robin Ru -
2017 : Cost-sensitive detection with variational autoencoders for environmental acoustic sensing »
Yunpeng Li · Stephen J Roberts -
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 : Poster Session (encompasses coffee break) »
Beidi Chen · Borja Balle · Daniel Lee · iuri frosio · Jitendra Malik · Jan Kautz · Ke Li · Masashi Sugiyama · Miguel A. Carreira-Perpinan · Ramin Raziperchikolaei · Theja Tulabandhula · Yung-Kyun Noh · Adams Wei Yu -
2017 : Poster Session »
Shunsuke Horii · Heejin Jeong · Tobias Schwedes · Qing He · Ben Calderhead · Ertunc Erdil · Jaan Altosaar · Patrick Muchmore · Rajiv Khanna · Ian Gemp · Pengfei Zhang · Yuan Zhou · Chris Cremer · Maria DeYoreo · Alexander Terenin · Brendan McVeigh · Rachit Singh · Yaodong Yang · Erik Bodin · Trefor Evans · Henry Chai · Shandian Zhe · Jeffrey Ling · Vincent ADAM · Lars Maaløe · Andrew Miller · Ari Pakman · Josip Djolonga · Hong Ge -
2017 : Contributed talk: Safe Policy Search with Gaussian Process Models »
Kyriakos Polymenakos · Stephen J Roberts -
2017 : Contributed talk: Learning Implicit Generative Models Using Differentiable Graph Tests »
Josip Djolonga -
2017 : On Structured Prediction Theory with Calibrated Convex Surrogate Losses. »
Simon Lacoste-Julien -
2017 Poster: Breaking the Nonsmooth Barrier: A Scalable Parallel Method for Composite Optimization »
Fabian Pedregosa · Rémi Leblond · Simon Lacoste-Julien -
2017 Poster: On Structured Prediction Theory with Calibrated Convex Surrogate Losses »
Anton Osokin · Francis Bach · Simon Lacoste-Julien -
2017 Poster: f-GANs in an Information Geometric Nutshell »
Richard Nock · Zac Cranko · Aditya K Menon · Lizhen Qu · Robert Williamson -
2017 Poster: Variance-based Regularization with Convex Objectives »
Hongseok Namkoong · John Duchi -
2017 Poster: The Marginal Value of Adaptive Gradient Methods in Machine Learning »
Ashia C Wilson · Becca Roelofs · Mitchell Stern · Nati Srebro · Benjamin Recht -
2017 Poster: Clustering with Noisy Queries »
Arya Mazumdar · Barna Saha -
2017 Poster: Spectrally-normalized margin bounds for neural networks »
Peter Bartlett · Dylan J Foster · Matus Telgarsky -
2017 Spotlight: Breaking the Nonsmooth Barrier: A Scalable Parallel Method for Composite Optimization »
Fabian Pedregosa · Rémi Leblond · Simon Lacoste-Julien -
2017 Oral: The Marginal Value of Adaptive Gradient Methods in Machine Learning »
Ashia C Wilson · Becca Roelofs · Mitchell Stern · Nati Srebro · Benjamin Recht -
2017 Spotlight: Spectrally-normalized margin bounds for neural networks »
Peter Bartlett · Dylan J Foster · Matus Telgarsky -
2017 Spotlight: f-GANs in an Information Geometric Nutshell »
Richard Nock · Zac Cranko · Aditya K Menon · Lizhen Qu · Robert Williamson -
2017 Oral: Variance-based Regularization with Convex Objectives »
Hongseok Namkoong · John Duchi -
2017 Oral: On Structured Prediction Theory with Calibrated Convex Surrogate Losses »
Anton Osokin · Francis Bach · Simon Lacoste-Julien -
2017 Poster: Greedy Algorithms for Cone Constrained Optimization with Convergence Guarantees »
Francesco Locatello · Michael Tschannen · Gunnar Ratsch · Martin Jaggi -
2017 Poster: Differentiable Learning of Submodular Functions »
Josip Djolonga · Andreas Krause -
2017 Poster: Stochastic Approximation for Canonical Correlation Analysis »
Raman Arora · Teodor Vanislavov Marinov · Poorya Mianjy · Nati Srebro -
2017 Poster: Exploring Generalization in Deep Learning »
Behnam Neyshabur · Srinadh Bhojanapalli · David Mcallester · Nati Srebro -
2017 Poster: Parameter-Free Online Learning via Model Selection »
Dylan J Foster · Satyen Kale · Mehryar Mohri · Karthik Sridharan -
2017 Poster: Implicit Regularization in Matrix Factorization »
Suriya Gunasekar · Blake Woodworth · Srinadh Bhojanapalli · Behnam Neyshabur · Nati Srebro -
2017 Poster: Semisupervised Clustering, AND-Queries and Locally Encodable Source Coding »
Arya Mazumdar · Soumyabrata Pal -
2017 Spotlight: Parameter-Free Online Learning via Model Selection »
Dylan J Foster · Satyen Kale · Mehryar Mohri · Karthik Sridharan -
2017 Spotlight: Differentiable Learning of Submodular Functions »
Josip Djolonga · Andreas Krause -
2017 Spotlight: Semisupervised Clustering, AND-Queries and Locally Encodable Source Coding »
Arya Mazumdar · Soumyabrata Pal -
2017 Spotlight: Implicit Regularization in Matrix Factorization »
Suriya Gunasekar · Blake Woodworth · Srinadh Bhojanapalli · Behnam Neyshabur · Nati Srebro -
2017 Poster: Soft-to-Hard Vector Quantization for End-to-End Learning Compressible Representations »
Eirikur Agustsson · Fabian Mentzer · Michael Tschannen · Lukas Cavigelli · Radu Timofte · Luca Benini · Luc V Gool -
2017 Poster: Generative Local Metric Learning for Kernel Regression »
Yung-Kyun Noh · Masashi Sugiyama · Kee-Eung Kim · Frank Park · Daniel Lee -
2017 Poster: Query Complexity of Clustering with Side Information »
Arya Mazumdar · Barna Saha -
2017 Poster: AdaGAN: Boosting Generative Models »
Ilya Tolstikhin · Sylvain Gelly · Olivier Bousquet · Carl-Johann SIMON-GABRIEL · Bernhard Schölkopf -
2017 Poster: Unsupervised Transformation Learning via Convex Relaxations »
Tatsunori Hashimoto · Percy Liang · John Duchi -
2017 Poster: Maxing and Ranking with Few Assumptions »
Moein Falahatgar · Yi Hao · Alon Orlitsky · Venkatadheeraj Pichapati · Vaishakh Ravindrakumar -
2016 Poster: Local Minimax Complexity of Stochastic Convex Optimization »
sabyasachi chatterjee · John Duchi · John Lafferty · Yuancheng Zhu -
2016 Poster: Avoiding Imposters and Delinquents: Adversarial Crowdsourcing and Peer Prediction »
Jacob Steinhardt · Gregory Valiant · Moses Charikar -
2016 Poster: Tight Complexity Bounds for Optimizing Composite Objectives »
Blake Woodworth · Nati Srebro -
2016 Poster: Variational Inference in Mixed Probabilistic Submodular Models »
Josip Djolonga · Sebastian Tschiatschek · Andreas Krause -
2016 Poster: Bayesian Optimization for Probabilistic Programs »
Thomas Rainforth · Tuan Anh Le · Jan-Willem van de Meent · Michael A Osborne · Frank Wood -
2016 Poster: Efficient Globally Convergent Stochastic Optimization for Canonical Correlation Analysis »
Weiran Wang · Jialei Wang · Dan Garber · Dan Garber · Nati Srebro -
2016 Poster: Learning in Games: Robustness of Fast Convergence »
Dylan Foster · zhiyuan li · Thodoris Lykouris · Karthik Sridharan · Eva Tardos -
2016 Poster: DeepMath - Deep Sequence Models for Premise Selection »
Geoffrey Irving · Christian Szegedy · Alexander Alemi · Niklas Een · Francois Chollet · Josef Urban -
2016 Poster: Global Optimality of Local Search for Low Rank Matrix Recovery »
Srinadh Bhojanapalli · Behnam Neyshabur · Nati Srebro -
2016 Poster: Path-Normalized Optimization of Recurrent Neural Networks with ReLU Activations »
Behnam Neyshabur · Yuhuai Wu · Russ Salakhutdinov · Nati Srebro -
2016 Poster: Stochastic Gradient Methods for Distributionally Robust Optimization with f-divergences »
Hongseok Namkoong · John Duchi -
2016 Poster: Variational Information Maximization for Feature Selection »
Shuyang Gao · Greg Ver Steeg · Aram Galstyan -
2016 Poster: Cooperative Graphical Models »
Josip Djolonga · Stefanie Jegelka · Sebastian Tschiatschek · Andreas Krause -
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: Normalized Spectral Map Synchronization »
Yanyao Shen · Qixing Huang · Nati Srebro · Sujay Sanghavi -
2016 Poster: Learning Kernels with Random Features »
Aman Sinha · John Duchi -
2015 : Discussion Panel »
Tim van Erven · Wouter Koolen · Peter Grünwald · Shai Ben-David · Dylan Foster · Satyen Kale · Gergely Neu -
2015 : Adaptive Online Learning »
Dylan Foster -
2015 Workshop: Probabilistic Integration »
Michael A Osborne · Philipp Hennig -
2015 Symposium: Algorithms Among Us: the Societal Impacts of Machine Learning »
Michael A Osborne · Adrian Weller · Murray Shanahan -
2015 Poster: Asynchronous stochastic convex optimization: the noise is in the noise and SGD don't care »
Sorathan Chaturapruek · John Duchi · Christopher Ré -
2015 Poster: Learning with Symmetric Label Noise: The Importance of Being Unhinged »
Brendan van Rooyen · Aditya Menon · Robert Williamson -
2015 Spotlight: Learning with Symmetric Label Noise: The Importance of Being Unhinged »
Brendan van Rooyen · Aditya Menon · Robert Williamson -
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: 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: Adaptive Online Learning »
Dylan Foster · Alexander Rakhlin · Karthik Sridharan -
2015 Spotlight: Adaptive Online Learning »
Dylan Foster · Alexander Rakhlin · Karthik Sridharan -
2015 Poster: Path-SGD: Path-Normalized Optimization in Deep Neural Networks »
Behnam Neyshabur · Russ Salakhutdinov · Nati Srebro -
2015 Poster: Frank-Wolfe Bayesian Quadrature: Probabilistic Integration with Theoretical Guarantees »
François-Xavier Briol · Chris Oates · Mark Girolami · Michael A Osborne -
2015 Spotlight: Frank-Wolfe Bayesian Quadrature: Probabilistic Integration with Theoretical Guarantees »
François-Xavier Briol · Chris Oates · Mark Girolami · Michael A Osborne -
2015 Poster: Rethinking LDA: Moment Matching for Discrete ICA »
Anastasia Podosinnikova · Francis Bach · Simon Lacoste-Julien -
2014 Poster: Discovering Structure in High-Dimensional Data Through Correlation Explanation »
Greg Ver Steeg · Aram Galstyan -
2014 Poster: From Stochastic Mixability to Fast Rates »
Nishant Mehta · Robert Williamson -
2014 Poster: From MAP to Marginals: Variational Inference in Bayesian Submodular Models »
Josip Djolonga · Andreas Krause -
2014 Poster: Sampling for Inference in Probabilistic Models with Fast Bayesian Quadrature »
Tom Gunter · Michael A Osborne · Roman Garnett · Philipp Hennig · Stephen J Roberts -
2014 Oral: From Stochastic Mixability to Fast Rates »
Nishant Mehta · Robert Williamson -
2014 Poster: Stochastic Gradient Descent, Weighted Sampling, and the Randomized Kaczmarz algorithm »
Deanna Needell · Rachel Ward · Nati Srebro -
2014 Poster: SAGA: A Fast Incremental Gradient Method With Support for Non-Strongly Convex Composite Objectives »
Aaron Defazio · Francis Bach · Simon Lacoste-Julien -
2013 Workshop: Learning Faster From Easy Data »
Peter Grünwald · Wouter M Koolen · Sasha Rakhlin · Nati Srebro · Alekh Agarwal · Karthik Sridharan · Tim van Erven · Sebastien Bubeck -
2013 Workshop: Bayesian Optimization in Theory and Practice »
Matthew Hoffman · Jasper Snoek · Nando de Freitas · Michael A Osborne · Ryan Adams · Sebastien Bubeck · Philipp Hennig · Remi Munos · Andreas Krause -
2013 Workshop: Large Scale Matrix Analysis and Inference »
Reza Zadeh · Gunnar Carlsson · Michael Mahoney · Manfred K. Warmuth · Wouter M Koolen · Nati Srebro · Satyen Kale · Malik Magdon-Ismail · Ashish Goel · Matei A Zaharia · David Woodruff · Ioannis Koutis · Benjamin Recht -
2013 Poster: High-Dimensional Gaussian Process Bandits »
Josip Djolonga · Andreas Krause · Volkan Cevher -
2013 Poster: Information-theoretic lower bounds for distributed statistical estimation with communication constraints »
Yuchen Zhang · John Duchi · Michael Jordan · Martin J Wainwright -
2013 Oral: Information-theoretic lower bounds for distributed statistical estimation with communication constraints »
Yuchen Zhang · John Duchi · Michael Jordan · Martin J Wainwright -
2013 Poster: Stochastic Optimization of PCA with Capped MSG »
Raman Arora · Andrew Cotter · Nati Srebro -
2013 Poster: Auditing: Active Learning with Outcome-Dependent Query Costs »
Sivan Sabato · Anand D Sarwate · Nati Srebro -
2013 Poster: Local Privacy and Minimax Bounds: Sharp Rates for Probability Estimation »
John Duchi · Martin J Wainwright · Michael Jordan -
2013 Poster: The Power of Asymmetry in Binary Hashing »
Behnam Neyshabur · Nati Srebro · Russ Salakhutdinov · Yury Makarychev · Payman Yadollahpour -
2013 Poster: Estimation, Optimization, and Parallelism when Data is Sparse »
John Duchi · Michael Jordan · Brendan McMahan -
2012 Workshop: Probabilistic Numerics »
Philipp Hennig · John P Cunningham · Michael A Osborne -
2012 Workshop: Big Learning : Algorithms, Systems, and Tools »
Sameer Singh · John Duchi · Yucheng Low · Joseph E Gonzalez -
2012 Poster: Sparse Prediction with the $k$-Support Norm »
Andreas Argyriou · Rina Foygel · Nati Srebro -
2012 Spotlight: Sparse Prediction with the $k$-Support Norm »
Andreas Argyriou · Rina Foygel · Nati Srebro -
2012 Poster: Privacy Aware Learning »
John Duchi · Michael Jordan · Martin J Wainwright -
2012 Poster: Communication-Efficient Algorithms for Statistical Optimization »
Yuchen Zhang · John Duchi · Martin J Wainwright -
2012 Poster: Mixability in Statistical Learning »
Tim van Erven · Peter Grünwald · Mark Reid · Robert Williamson -
2012 Oral: Privacy Aware Learning »
John Duchi · Michael Jordan · Martin J Wainwright -
2012 Poster: Matrix reconstruction with the local max norm »
Rina Foygel · Nati Srebro · Russ Salakhutdinov -
2012 Poster: Finite Sample Convergence Rates of Zero-Order Stochastic Optimization Methods »
John Duchi · Michael Jordan · Martin J Wainwright · Andre Wibisono -
2012 Poster: Diffusion Decision Making for Adaptive k-Nearest Neighbor Classification »
Yung-Kyun Noh · Frank Park · Daniel Lee -
2012 Poster: Active Learning of Model Evidence Using Bayesian Quadrature »
Michael A Osborne · David Duvenaud · Roman Garnett · Carl Edward Rasmussen · Stephen J Roberts · Zoubin Ghahramani -
2011 Workshop: Bayesian optimization, experimental design and bandits: Theory and applications »
Nando de Freitas · Roman Garnett · Frank R Hutter · Michael A Osborne -
2011 Workshop: Relations between machine learning problems - an approach to unify the field »
Robert Williamson · John Langford · Ulrike von Luxburg · Mark Reid · Jennifer Wortman Vaughan -
2011 Poster: Beating SGD: Learning SVMs in Sublinear Time »
Elad Hazan · Tomer Koren · Nati Srebro -
2011 Poster: Distributed Delayed Stochastic Optimization »
Alekh Agarwal · John Duchi -
2011 Poster: Better Mini-Batch Algorithms via Accelerated Gradient Methods »
Andrew Cotter · Ohad Shamir · Nati Srebro · Karthik Sridharan -
2011 Poster: Comparative Analysis of Viterbi Training and Maximum Likelihood Estimation for HMMs »
Armen Allahverdyan · Aram Galstyan -
2011 Poster: Composite Multiclass Losses »
Elodie Vernet · Robert Williamson · Mark Reid -
2011 Poster: On the Universality of Online Mirror Descent »
Nati Srebro · Karthik Sridharan · Ambuj Tewari -
2011 Poster: Learning with the weighted trace-norm under arbitrary sampling distributions »
Rina Foygel · Russ Salakhutdinov · Ohad Shamir · Nati Srebro -
2010 Workshop: Learning on Cores, Clusters, and Clouds »
Alekh Agarwal · Lawrence Cayton · Ofer Dekel · John Duchi · John Langford -
2010 Session: Spotlights Session 11 »
Nati Srebro -
2010 Session: Oral Session 13 »
Nati Srebro -
2010 Spotlight: Distributed Dual Averaging In Networks »
John Duchi · Alekh Agarwal · Martin J Wainwright -
2010 Poster: Tight Sample Complexity of Large-Margin Learning »
Sivan Sabato · Nati Srebro · Naftali Tishby -
2010 Poster: Distributed Dual Averaging In Networks »
John Duchi · Alekh Agarwal · Martin J Wainwright -
2010 Poster: Collaborative Filtering in a Non-Uniform World: Learning with the Weighted Trace Norm »
Russ Salakhutdinov · Nati Srebro -
2010 Poster: Practical Large-Scale Optimization for Max-norm Regularization »
Jason D Lee · Benjamin Recht · Russ Salakhutdinov · Nati Srebro · Joel A Tropp -
2010 Poster: Smoothness, Low Noise and Fast Rates »
Nati Srebro · Karthik Sridharan · Ambuj Tewari -
2010 Poster: Generative Local Metric Learning for Nearest Neighbor Classification »
Yung-Kyun Noh · Byoung-Tak Zhang · Daniel Lee -
2009 Workshop: The Generative and Discriminative Learning Interface »
Simon Lacoste-Julien · Percy Liang · Guillaume Bouchard -
2009 Workshop: Clustering: Science or art? Towards principled approaches »
Margareta Ackerman · Shai Ben-David · Avrim Blum · Isabelle Guyon · Ulrike von Luxburg · Robert Williamson · Reza Zadeh -
2009 Workshop: Understanding Multiple Kernel Learning Methods »
Brian McFee · Gert Lanckriet · Francis Bach · Nati Srebro -
2009 Poster: Efficient Learning using Forward-Backward Splitting »
John Duchi · Yoram Singer -
2009 Poster: Statistical Analysis of Semi-Supervised Learning: The Limit of Infinite Unlabelled Data »
Boaz Nadler · Nati Srebro · Xueyuan Zhou -
2009 Spotlight: Statistical Analysis of Semi-Supervised Learning: The Limit of Infinite Unlabelled Data »
Boaz Nadler · Nati Srebro · Xueyuan Zhou -
2009 Oral: Efficient Learning using Forward-Backward Splitting »
John Duchi · Yoram Singer -
2008 Poster: Fast Rates for Regularized Objectives »
Karthik Sridharan · Shai Shalev-Shwartz · Nati Srebro -
2008 Poster: DiscLDA: Discriminative Learning for Dimensionality Reduction and Classification »
Simon Lacoste-Julien · Fei Sha · Michael Jordan -
2006 Poster: Bayesian Image Super-resolution, Continued »
Lyndsey C Pickup · David Capel · Stephen J Roberts · Andrew Zisserman -
2006 Spotlight: Bayesian Image Super-resolution, Continued »
Lyndsey C Pickup · David Capel · Stephen J Roberts · Andrew Zisserman -
2006 Poster: Using Combinatorial Optimization within Max-Product Belief Propagation »
John Duchi · Danny Tarlow · Gal Elidan · Daphne Koller -
2006 Spotlight: Using Combinatorial Optimization within Max-Product Belief Propagation »
John Duchi · Danny Tarlow · Gal Elidan · Daphne Koller