Timezone: »
Author Information
Yejin Choi (University of Washington)
Alexei Efros (UC Berkeley)
Chelsea Finn (Stanford)
Kristen Grauman (University of Texas at Austin)
Quoc V Le (Google)
Yann LeCun (Facebook AI Research and New York University)
Yann LeCun is Director of AI Research at Facebook, and Silver Professor of Data Science, Computer Science, Neural Science, and Electrical Engineering at New York University. He received the Electrical Engineer Diploma from ESIEE, Paris in 1983, and a PhD in Computer Science from Université Pierre et Marie Curie (Paris) in 1987. After a postdoc at the University of Toronto, he joined AT&T Bell Laboratories in Holmdel, NJ in 1988. He became head of the Image Processing Research Department at AT&T Labs-Research in 1996, and joined NYU as a professor in 2003, after a brief period as a Fellow of the NEC Research Institute in Princeton. From 2012 to 2014 he directed NYU's initiative in data science and became the founding director of the NYU Center for Data Science. He was named Director of AI Research at Facebook in late 2013 and retains a part-time position on the NYU faculty. His current interests include AI, machine learning, computer perception, mobile robotics, and computational neuroscience. He has published over 180 technical papers and book chapters on these topics as well as on neural networks, handwriting recognition, image processing and compression, and on dedicated circuits for computer perception.
Ruslan Salakhutdinov (Carnegie Mellon University)
Eric Xing (Petuum Inc. / Carnegie Mellon University)
More from the Same Authors
-
2021 : MultiBench: Multiscale Benchmarks for Multimodal Representation Learning »
Paul Pu Liang · Yiwei Lyu · Xiang Fan · Zetian Wu · Yun Cheng · Jason Wu · Leslie (Yufan) Chen · Peter Wu · Michelle A. Lee · Yuke Zhu · Ruslan Salakhutdinov · Louis-Philippe Morency -
2021 : CommonsenseQA 2.0: Exposing the Limits of AI through Gamification »
Alon Talmor · Ori Yoran · Ronan Le Bras · Chandra Bhagavatula · Yoav Goldberg · Yejin Choi · Jonathan Berant -
2021 : NaturalProofs: Mathematical Theorem Proving in Natural Language »
Sean Welleck · Jiacheng Liu · Ronan Le Bras · Hanna Hajishirzi · Yejin Choi · Kyunghyun Cho -
2021 Spotlight: Shaping embodied agent behavior with activity-context priors from egocentric video »
Tushar Nagarajan · Kristen Grauman -
2021 Spotlight: Efficiently Identifying Task Groupings for Multi-Task Learning »
Chris Fifty · Ehsan Amid · Zhe Zhao · Tianhe Yu · Rohan Anil · Chelsea Finn -
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 : Bridge Data: Boosting Generalization of Robotic Skills with Cross-Domain Datasets »
Frederik Ebert · Yanlai Yang · Karl Schmeckpeper · Bernadette Bucher · Kostas Daniilidis · Chelsea Finn · Sergey Levine -
2021 : Lifelong Robotic Reinforcement Learning by Retaining Experiences »
Annie Xie · Chelsea Finn -
2021 : Towards Grounded Natural Language Proof Generation »
Sean Welleck · Jiacheng Liu · Yejin Choi -
2021 : Correct-N-Contrast: A Contrastive Approach for Improving Robustness to Spurious Correlations »
Michael Zhang · Nimit Sohoni · Hongyang Zhang · Chelsea Finn · Christopher Ré -
2021 : Extending the WILDS Benchmark for Unsupervised Adaptation »
Shiori Sagawa · Pang Wei Koh · Tony Lee · Irena Gao · Sang Michael Xie · Kendrick Shen · Ananya Kumar · Weihua Hu · Michihiro Yasunaga · Henrik Marklund · Sara Beery · Ian Stavness · Jure Leskovec · Kate Saenko · Tatsunori Hashimoto · Sergey Levine · Chelsea Finn · Percy Liang -
2021 : Test Time Robustification of Deep Models via Adaptation and Augmentation »
Marvin Zhang · Sergey Levine · Chelsea Finn -
2021 : The Reflective Explorer: Online Meta-Exploration from Offline Data in Realistic Robotic Tasks »
Rafael Rafailov · · Tianhe Yu · Avi Singh · Mariano Phielipp · Chelsea Finn -
2021 : Data Sharing without Rewards in Multi-Task Offline Reinforcement Learning »
Tianhe Yu · Aviral Kumar · Yevgen Chebotar · Chelsea Finn · Sergey Levine · Karol Hausman -
2021 : CoMPS: Continual Meta Policy Search »
Glen Berseth · Zhiwei Zhang · Grace Zhang · Chelsea Finn · Sergey Levine -
2021 : Discriminator Augmented Model-Based Reinforcement Learning »
Allan Zhou · Archit Sharma · Chelsea Finn -
2021 : Multi-modal Self-supervised Pre-training for Large-scale Genome Data »
Shentong Mo · Xi Fu · Chenyang Hong · Yizhen Chen · Yuxuan Zheng · Xiangru Tang · Yanyan Lan · Zhiqiang Shen · Eric Xing -
2021 : Curiosity with Chelsea Finn, Celeste Kidd, Timothy Verstynen »
Celeste Kidd · Chelsea Finn · Timothy Verstynen · Johnathan Flowers -
2021 : Example-Based Offline Reinforcement Learning without Rewards »
Kyle Hatch · Tianhe Yu · Rafael Rafailov · Chelsea Finn -
2021 : The Reflective Explorer: Online Meta-Exploration from Offline Data in Realistic Robotic Tasks »
Rafael Rafailov · · Tianhe Yu · Avi Singh · Mariano Phielipp · Chelsea Finn -
2022 Poster: LAPO: Latent-Variable Advantage-Weighted Policy Optimization for Offline Reinforcement Learning »
Xi Chen · Ali Ghadirzadeh · Tianhe Yu · Jianhao Wang · Alex Yuan Gao · Wenzhe Li · Liang Bin · Chelsea Finn · Chongjie Zhang -
2022 : You Only Live Once: Single-Life Reinforcement Learning »
Annie Chen · Archit Sharma · Sergey Levine · Chelsea Finn -
2022 : What Makes Certain Pre-Trained Visual Representations Better for Robotic Learning? »
Kyle Hsu · Tyler Lum · Ruohan Gao · Shixiang (Shane) Gu · Jiajun Wu · Chelsea Finn -
2022 : A Control-Centric Benchmark for Video Prediction »
Stephen Tian · Chelsea Finn · Jiajun Wu -
2022 : Pre-Training for Robots: Leveraging Diverse Multitask Data via Offline Reinforcement Learning »
Aviral Kumar · Anikait Singh · Frederik Ebert · Yanlai Yang · Chelsea Finn · Sergey Levine -
2022 : Train Offline, Test Online: A Real Robot Learning Benchmark »
Gaoyue Zhou · Victoria Dean · Mohan Kumar Srirama · Aravind Rajeswaran · Jyothish Pari · Kyle Hatch · Aryan Jain · Tianhe Yu · Pieter Abbeel · Lerrel Pinto · Chelsea Finn · Abhinav Gupta -
2022 : Bitrate-Constrained DRO: Beyond Worst Case Robustness To Unknown Group Shifts »
Amrith Setlur · Don Dennis · Benjamin Eysenbach · Aditi Raghunathan · Chelsea Finn · Virginia Smith · Sergey Levine -
2022 : Train Offline, Test Online: A Real Robot Learning Benchmark »
Gaoyue Zhou · Victoria Dean · Mohan Kumar Srirama · Aravind Rajeswaran · Jyothish Pari · Kyle Hatch · Aryan Jain · Tianhe Yu · Pieter Abbeel · Lerrel Pinto · Chelsea Finn · Abhinav Gupta -
2022 : Multi-Domain Long-Tailed Learning by Augmenting Disentangled Representations »
Huaxiu Yao · Xinyu Yang · Allan Zhou · Chelsea Finn -
2022 : Surgical Fine-Tuning Improves Adaptation to Distribution Shifts »
Yoonho Lee · Annie Chen · Fahim Tajwar · Ananya Kumar · Huaxiu Yao · Percy Liang · Chelsea Finn -
2022 : Contrastive Example-Based Control »
Kyle Hatch · Sarthak J Shetty · Benjamin Eysenbach · Tianhe Yu · Rafael Rafailov · Russ Salakhutdinov · Sergey Levine · Chelsea Finn -
2022 : Train Offline, Test Online: A Real Robot Learning Benchmark »
Gaoyue Zhou · Victoria Dean · Mohan Kumar Srirama · Aravind Rajeswaran · Jyothish Pari · Kyle Hatch · Aryan Jain · Tianhe Yu · Pieter Abbeel · Lerrel Pinto · Chelsea Finn · Abhinav Gupta -
2022 : Relaxing the Kolmogorov Structure Function for Realistic Computational Constraints »
Yoonho Lee · Chelsea Finn · Stefano Ermon -
2022 : Information-Theoretic Evaluation of Free-Text Rationales with Conditional $\mathcal{V}$-Information »
Hanjie Chen · Faeze Brahman · Xiang Ren · Yangfeng Ji · Yejin Choi · Swabha Swayamdipta -
2022 : Studying Bias in GANs through the Lens of Race »
Vongani Maluleke · Neerja Thakkar · Tim Brooks · Ethan Weber · Trevor Darrell · Alexei Efros · Angjoo Kanazawa · Devin Guillory -
2022 : Recommendation for New Drugs with Limited Prescription Data »
Zhenbang Wu · Huaxiu Yao · Zhe Su · David Liebovitz · Lucas Glass · James Zou · Chelsea Finn · Jimeng Sun -
2022 : What Makes Certain Pre-Trained Visual Representations Better for Robotic Learning? »
Kyle Hsu · Tyler Lum · Ruohan Gao · Shixiang (Shane) Gu · Jiajun Wu · Chelsea Finn -
2022 : Train Offline, Test Online: A Real Robot Learning Benchmark »
Gaoyue Zhou · Victoria Dean · Mohan Kumar Srirama · Aravind Rajeswaran · Jyothish Pari · Kyle Hatch · Aryan Jain · Tianhe Yu · Pieter Abbeel · Lerrel Pinto · Chelsea Finn · Abhinav Gupta -
2022 : Pre-Training for Robots: Leveraging Diverse Multitask Data via Offline Reinforcement Learning »
Anikait Singh · Aviral Kumar · Frederik Ebert · Yanlai Yang · Chelsea Finn · Sergey Levine -
2022 : Fine-tuning Offline Policies with Optimistic Action Selection »
Max Sobol Mark · Ali Ghadirzadeh · Xi Chen · Chelsea Finn -
2022 : Policy Architectures for Compositional Generalization in Control »
Allan Zhou · Vikash Kumar · Chelsea Finn · Aravind Rajeswaran -
2022 : Contrastive Example-Based Control »
Kyle Hatch · Sarthak J Shetty · Benjamin Eysenbach · Tianhe Yu · Rafael Rafailov · Russ Salakhutdinov · Sergey Levine · Chelsea Finn -
2022 : Giving Robots a Hand: Broadening Generalization via Hand-Centric Human Video Demonstrations »
Moo J Kim · Jiajun Wu · Chelsea Finn -
2022 : Simplifying Model-based RL: Learning Representations, Latent-space Models, and Policies with One Objective »
Raj Ghugare · Homanga Bharadhwaj · Benjamin Eysenbach · Sergey Levine · Ruslan Salakhutdinov -
2022 : MultiViz: Towards Visualizing and Understanding Multimodal Models »
Paul Pu Liang · · Gunjan Chhablani · Nihal Jain · Zihao Deng · Xingbo Wang · Louis-Philippe Morency · Ruslan Salakhutdinov -
2022 : Nano: Nested Human-in-the-Loop Reward Learning for Controlling Distribution of Generated Text »
Xiang Fan · · Paul Pu Liang · Ruslan Salakhutdinov · Louis-Philippe Morency -
2022 : Surgical Fine-Tuning Improves Adaptation to Distribution Shifts »
Yoonho Lee · Annie Chen · Fahim Tajwar · Ananya Kumar · Huaxiu Yao · Percy Liang · Chelsea Finn -
2022 : Exploring Transformer Backbones for Heterogeneous Treatment Effect Estimation »
yifan zhang · Hanlin Zhang · Zachary Lipton · Li Erran Li · Eric Xing -
2022 : Train Offline, Test Online: A Real Robot Learning Benchmark »
Gaoyue Zhou · Victoria Dean · Mohan Kumar Srirama · Aravind Rajeswaran · Jyothish Pari · Kyle Hatch · Aryan Jain · Tianhe Yu · Pieter Abbeel · Lerrel Pinto · Chelsea Finn · Abhinav Gupta -
2023 Poster: EgoEnv: Human-centric environment representations from egocentric video »
Tushar Nagarajan · Santhosh Kumar Ramakrishnan · Ruta Desai · James Hillis · Kristen Grauman -
2023 Poster: Diffusion Self-Guidance for Controllable Image Generation »
Dave Epstein · Allan Jabri · Ben Poole · Alexei Efros · Aleksander Holynski -
2023 Poster: Symbolic Discovery of Optimization Algorithms »
Xiangning Chen · Chen Liang · Da Huang · Esteban Real · Kaiyuan Wang · Hieu Pham · Xuanyi Dong · Thang Luong · Cho-Jui Hsieh · Yifeng Lu · Quoc V Le -
2023 Poster: DoReMi: Optimizing Data Mixtures Speeds Up Language Model Pretraining »
Sang Michael Xie · Hieu Pham · Xuanyi Dong · Nan Du · Hanxiao Liu · Yifeng Lu · Percy Liang · Quoc V Le · Tengyu Ma · Adams Wei Yu -
2023 Poster: Permutation Equivariant Neural Functionals »
Allan Zhou · Kaien Yang · Kaylee Burns · Adriano Cardace · Yiding Jiang · Samuel Sokota · J. Zico Kolter · Chelsea Finn -
2023 Poster: In-Context Decision-Making from Supervised Pretraining »
Jonathan N Lee · Annie Xie · Aldo Pacchiano · Yash Chandak · Chelsea Finn · Ofir Nachum · Emma Brunskill -
2023 Poster: Self-Supervised Visual Acoustic Matching »
Arjun Somayazulu · Changan Chen · Kristen Grauman -
2023 Poster: Factorized Contrastive Learning: Going Beyond Multi-view Redundancy »
Paul Pu Liang · Zihao Deng · Martin Q. Ma · James Zou · Louis-Philippe Morency · Ruslan Salakhutdinov -
2023 Poster: Self-Supervised Learning with Lie Symmetries for Partial Differential Equations »
Grégoire Mialon · Quentin Garrido · Hannah Lawrence · Danyal Rehman · Bobak Kiani · Yann LeCun -
2023 Poster: Video-Mined Task Graphs for Keystep Recognition in Instructional Videos »
Kumar Ashutosh · Santhosh Kumar Ramakrishnan · Triantafyllos Afouras · Kristen Grauman -
2023 Poster: Localized Symbolic Knowledge Distillation for Visual Commonsense Models »
Jae Sung Park · Jack Hessel · Khyathi Chandu · Paul Pu Liang · Ximing Lu · Qiuyuan Huang · Peter West · Jianfeng Gao · Ali Farhadi · Yejin Choi -
2023 Poster: SwiftSage: A Generative Agent with Fast and Slow Thinking for Complex Interactive Tasks »
Bill Yuchen Lin · Yicheng Fu · Karina Yang · Prithviraj (Raj) Ammanabrolu · Faeze Brahman · Shiyu Huang · Chandra Bhagavatula · Yejin Choi · Xiang Ren -
2023 Poster: Learning Fine-grained View-Invariant Representations from Unpaired Ego-Exo Videos via Temporal Alignment »
Zihui Xue · Kristen Grauman -
2023 Poster: EgoDistill: Egocentric Head Motion Distillation for Efficient Video Understanding »
Shuhan Tan · Tushar Nagarajan · Kristen Grauman -
2023 Poster: Reverse Engineering Self-Supervised Learning »
Ido Ben-Shaul · Ravid Shwartz-Ziv · Tomer Galanti · Shai Dekel · Yann LeCun -
2023 Poster: Disentanglement via Latent Quantization »
Kyle Hsu · William Dorrell · James Whittington · Chelsea Finn · Jiajun Wu -
2023 Poster: An Information Theory Perspective on Variance-Invariance-Covariance Regularization »
Ravid Shwartz-Ziv · Randall Balestriero · Kenji Kawaguchi · Tim G. J. Rudner · Yann LeCun -
2023 Poster: Neural Functional Transformers »
Allan Zhou · Kaien Yang · Yiding Jiang · Kaylee Burns · Winnie Xu · Samuel Sokota · J. Zico Kolter · Chelsea Finn -
2023 Poster: Direct Preference Optimization: Your Language Model is Secretly a Reward Model »
Rafael Rafailov · Archit Sharma · Eric Mitchell · Christopher D Manning · Stefano Ermon · Chelsea Finn -
2023 Poster: Cal-QL: Calibrated Offline RL Pre-Training for Efficient Online Fine-Tuning »
Mitsuhiko Nakamoto · Yuexiang Zhai · Anikait Singh · Max Sobol Mark · Yi Ma · Chelsea Finn · Aviral Kumar · Sergey Levine -
2023 Poster: Differentiable Blocks World: Qualitative 3D Decomposition by Rendering Primitives »
Tom Monnier · Jake Austin · Angjoo Kanazawa · Alexei Efros · Mathieu Aubry -
2023 Poster: Faith and Fate: Limits of Transformers on Compositionality »
Nouha Dziri · Ximing Lu · Melanie Sclar · Xiang (Lorraine) Li · Liwei Jiang · Bill Yuchen Lin · Sean Welleck · Peter West · Chandra Bhagavatula · Ronan Le Bras · Jena Hwang · Soumya Sanyal · Xiang Ren · Allyson Ettinger · Zaid Harchaoui · Yejin Choi -
2023 Poster: RoboCLIP: One Demonstration is Enough to Learn Robot Policies »
Sumedh Sontakke · Séb Arnold · Jesse Zhang · Karl Pertsch · Erdem Bıyık · Dorsa Sadigh · Chelsea Finn · Laurent Itti -
2023 Poster: Single-Stage Visual Query Localization in Egocentric Videos »
Hanwen Jiang · Santhosh Kumar Ramakrishnan · Kristen Grauman -
2023 Poster: Multimodal C4: An Open, Billion-scale Corpus of Images Interleaved with Text »
Wanrong Zhu · Jack Hessel · Anas Awadalla · Samir Yitzhak Gadre · Jesse Dodge · Alex Fang · Youngjae Yu · Ludwig Schmidt · William Yang Wang · Yejin Choi -
2023 Poster: RealTime QA: What's the Answer Right Now? »
Jungo Kasai · Keisuke Sakaguchi · yoichi takahashi · Ronan Le Bras · Akari Asai · Xinyan Yu · Dragomir Radev · Noah Smith · Yejin Choi · Kentaro Inui -
2023 Poster: EgoTracks: A Long-term Egocentric Visual Object Tracking Dataset »
Hao Tang · Kevin J Liang · Kristen Grauman · Matt Feiszli · Weiyao Wang -
2023 Oral: EgoEnv: Human-centric environment representations from egocentric video »
Tushar Nagarajan · Santhosh Kumar Ramakrishnan · Ruta Desai · James Hillis · Kristen Grauman -
2023 Oral: Direct Preference Optimization: Your Language Model is Secretly a Reward Model »
Rafael Rafailov · Archit Sharma · Eric Mitchell · Christopher D Manning · Stefano Ermon · Chelsea Finn -
2023 Competition: Train Offline, Test Online: A Democratized Robotics Benchmark »
Victoria Dean · Gaoyue Zhou · Mohan Kumar Srirama · Sudeep Dasari · Esther Brown · Marion Lepert · Paul Ruvolo · Chelsea Finn · Lerrel Pinto · Abhinav Gupta -
2023 Workshop: AI meets Moral Philosophy and Moral Psychology: An Interdisciplinary Dialogue about Computational Ethics »
Sydney Levine · Liwei Jiang · Jared Moore · Zhijing Jin · Yejin Choi -
2022 : Sample-Specific Contextualized Graphical Models Using Clinical and Molecular Data Reveal Transcriptional Network Heterogeneity Across 7000 Tumors »
Caleb Ellington · Ben Lengerich · Thomas Watkins · Jiekun Yang · Manolis Kellis · Eric Xing -
2022 : Train Offline, Test Online: A Real Robot Learning Benchmark »
Gaoyue Zhou · Victoria Dean · Mohan Kumar Srirama · Aravind Rajeswaran · Jyothish Pari · Kyle Hatch · Aryan Jain · Tianhe Yu · Pieter Abbeel · Lerrel Pinto · Chelsea Finn · Abhinav Gupta -
2022 : Train Offline, Test Online: A Real Robot Learning Benchmark »
Gaoyue Zhou · Victoria Dean · Mohan Kumar Srirama · Aravind Rajeswaran · Jyothish Pari · Kyle Hatch · Aryan Jain · Tianhe Yu · Pieter Abbeel · Lerrel Pinto · Chelsea Finn · Abhinav Gupta -
2022 Workshop: Workshop on Distribution Shifts: Connecting Methods and Applications »
Chelsea Finn · Fanny Yang · Hongseok Namkoong · Masashi Sugiyama · Jacob Eisenstein · Jonas Peters · Rebecca Roelofs · Shiori Sagawa · Pang Wei Koh · Yoonho Lee -
2022 Poster: The Effects of Regularization and Data Augmentation are Class Dependent »
Randall Balestriero · Leon Bottou · Yann LeCun -
2022 Poster: MEMO: Test Time Robustness via Adaptation and Augmentation »
Marvin Zhang · Sergey Levine · Chelsea Finn -
2022 Poster: Zero-shot Transfer Learning within a Heterogeneous Graph via Knowledge Transfer Networks »
Minji Yoon · John Palowitch · Dustin Zelle · Ziniu Hu · Ruslan Salakhutdinov · Bryan Perozzi -
2022 Poster: Learning Options via Compression »
Yiding Jiang · Evan Liu · Benjamin Eysenbach · J. Zico Kolter · Chelsea Finn -
2022 Poster: VICRegL: Self-Supervised Learning of Local Visual Features »
Adrien Bardes · Jean Ponce · Yann LeCun -
2022 Poster: Coarse-to-Fine Vision-Language Pre-training with Fusion in the Backbone »
Zi-Yi Dou · Aishwarya Kamath · Zhe Gan · Pengchuan Zhang · Jianfeng Wang · Linjie Li · Zicheng Liu · Ce Liu · Yann LeCun · Nanyun Peng · Jianfeng Gao · Lijuan Wang -
2022 Poster: COLD Decoding: Energy-based Constrained Text Generation with Langevin Dynamics »
Lianhui Qin · Sean Welleck · Daniel Khashabi · Yejin Choi -
2022 Poster: Pre-Train Your Loss: Easy Bayesian Transfer Learning with Informative Priors »
Ravid Shwartz-Ziv · Micah Goldblum · Hossein Souri · Sanyam Kapoor · Chen Zhu · Yann LeCun · Andrew Wilson -
2022 Poster: SoundSpaces 2.0: A Simulation Platform for Visual-Acoustic Learning »
Changan Chen · Carl Schissler · Sanchit Garg · Philip Kobernik · Alexander Clegg · Paul Calamia · Dhruv Batra · Philip Robinson · Kristen Grauman -
2022 Poster: A Data-Augmentation Is Worth A Thousand Samples: Analytical Moments And Sampling-Free Training »
Randall Balestriero · Ishan Misra · Yann LeCun -
2022 Poster: Mixture-of-Experts with Expert Choice Routing »
Yanqi Zhou · Tao Lei · Hanxiao Liu · Nan Du · Yanping Huang · Vincent Zhao · Andrew Dai · zhifeng Chen · Quoc V Le · James Laudon -
2022 Poster: projUNN: efficient method for training deep networks with unitary matrices »
Bobak Kiani · Randall Balestriero · Yann LeCun · Seth Lloyd -
2022 Poster: Few-Shot Audio-Visual Learning of Environment Acoustics »
Sagnik Majumder · Changan Chen · Ziad Al-Halah · Kristen Grauman -
2022 Poster: Chain-of-Thought Prompting Elicits Reasoning in Large Language Models »
Jason Wei · Xuezhi Wang · Dale Schuurmans · Maarten Bosma · brian ichter · Fei Xia · Ed Chi · Quoc V Le · Denny Zhou -
2022 Poster: You Only Live Once: Single-Life Reinforcement Learning »
Annie Chen · Archit Sharma · Sergey Levine · Chelsea Finn -
2022 Poster: Test-Time Training with Masked Autoencoders »
Yossi Gandelsman · Yu Sun · Xinlei Chen · Alexei Efros -
2022 Poster: Visual Prompting via Image Inpainting »
Amir Bar · Yossi Gandelsman · Trevor Darrell · Amir Globerson · Alexei Efros -
2022 Poster: Generating Long Videos of Dynamic Scenes »
Tim Brooks · Janne Hellsten · Miika Aittala · Ting-Chun Wang · Timo Aila · Jaakko Lehtinen · Ming-Yu Liu · Alexei Efros · Tero Karras -
2022 Poster: Wild-Time: A Benchmark of in-the-Wild Distribution Shift over Time »
Huaxiu Yao · Caroline Choi · Bochuan Cao · Yoonho Lee · Pang Wei Koh · Chelsea Finn -
2022 Poster: Contrastive and Non-Contrastive Self-Supervised Learning Recover Global and Local Spectral Embedding Methods »
Randall Balestriero · Yann LeCun -
2022 Poster: When to Ask for Help: Proactive Interventions in Autonomous Reinforcement Learning »
Annie Xie · Fahim Tajwar · Archit Sharma · Chelsea Finn -
2022 Poster: TabNAS: Rejection Sampling for Neural Architecture Search on Tabular Datasets »
Chengrun Yang · Gabriel Bender · Hanxiao Liu · Pieter-Jan Kindermans · Madeleine Udell · Yifeng Lu · Quoc V Le · Da Huang -
2022 Poster: C-Mixup: Improving Generalization in Regression »
Huaxiu Yao · Yiping Wang · Linjun Zhang · James Zou · Chelsea Finn -
2022 Poster: QUARK: Controllable Text Generation with Reinforced Unlearning »
Ximing Lu · Sean Welleck · Jack Hessel · Liwei Jiang · Lianhui Qin · Peter West · Prithviraj Ammanabrolu · Yejin Choi -
2022 Poster: Giving Feedback on Interactive Student Programs with Meta-Exploration »
Evan Liu · Moritz Stephan · Allen Nie · Chris Piech · Emma Brunskill · Chelsea Finn -
2022 Poster: NaturalProver: Grounded Mathematical Proof Generation with Language Models »
Sean Welleck · Jiacheng Liu · Ximing Lu · Hannaneh Hajishirzi · Yejin Choi -
2021 : Lifelong Robotic Reinforcement Learning by Retaining Experiences »
Annie Xie · Chelsea Finn -
2021 Workshop: Math AI for Education (MATHAI4ED): Bridging the Gap Between Research and Smart Education »
Pan Lu · Yuhuai Wu · Sean Welleck · Xiaodan Liang · Eric Xing · James McClelland -
2021 : Discussion: Chelsea Finn, Masashi Sugiyama »
Chelsea Finn · Masashi Sugiyama -
2021 : Robustness through the Lens of Invariance »
Chelsea Finn -
2021 : Panel Discussion »
Pascal Poupart · Ali Ghodsi · Luke Zettlemoyer · Sameer Singh · Kevin Duh · Yejin Choi · Lu Hou -
2021 : Battling with Larger Models through Grounding and Searching »
Yejin Choi -
2021 Workshop: Deep Reinforcement Learning »
Pieter Abbeel · Chelsea Finn · David Silver · Matthew Taylor · Martha White · Srijita Das · Yuqing Du · Andrew Patterson · Manan Tomar · Olivia Watkins -
2021 Oral: MERLOT: Multimodal Neural Script Knowledge Models »
Rowan Zellers · Ximing Lu · Jack Hessel · Youngjae Yu · Jae Sung Park · Jize Cao · Ali Farhadi · Yejin Choi -
2021 Poster: Visual Adversarial Imitation Learning using Variational Models »
Rafael Rafailov · Tianhe Yu · Aravind Rajeswaran · Chelsea Finn -
2021 : NaturalProofs: Mathematical Theorem Proving in Natural Language »
Sean Welleck · Jiacheng Liu · Ronan Le Bras · Hanna Hajishirzi · Yejin Choi · Kyunghyun Cho -
2021 Poster: Divergence Frontiers for Generative Models: Sample Complexity, Quantization Effects, and Frontier Integrals »
Lang Liu · Krishna Pillutla · Sean Welleck · Sewoong Oh · Yejin Choi · Zaid Harchaoui -
2021 Poster: Efficiently Identifying Task Groupings for Multi-Task Learning »
Chris Fifty · Ehsan Amid · Zhe Zhao · Tianhe Yu · Rohan Anil · Chelsea Finn -
2021 Poster: CoAtNet: Marrying Convolution and Attention for All Data Sizes »
Zihang Dai · Hanxiao Liu · Quoc V Le · Mingxing Tan -
2021 Poster: COMBO: Conservative Offline Model-Based Policy Optimization »
Tianhe Yu · Aviral Kumar · Rafael Rafailov · Aravind Rajeswaran · Sergey Levine · Chelsea Finn -
2021 Poster: MERLOT: Multimodal Neural Script Knowledge Models »
Rowan Zellers · Ximing Lu · Jack Hessel · Youngjae Yu · Jae Sung Park · Jize Cao · Ali Farhadi · Yejin Choi -
2021 Poster: Shaping embodied agent behavior with activity-context priors from egocentric video »
Tushar Nagarajan · Kristen Grauman -
2021 Poster: Searching for Efficient Transformers for Language Modeling »
David So · Wojciech Mańke · Hanxiao Liu · Zihang Dai · Noam Shazeer · Quoc V Le -
2021 Poster: Multi-task Learning of Order-Consistent Causal Graphs »
Xinshi Chen · Haoran Sun · Caleb Ellington · Eric Xing · Le Song -
2021 Poster: Information is Power: Intrinsic Control via Information Capture »
Nicholas Rhinehart · Jenny Wang · Glen Berseth · John Co-Reyes · Danijar Hafner · Chelsea Finn · Sergey Levine -
2021 Poster: Conservative Data Sharing for Multi-Task Offline Reinforcement Learning »
Tianhe Yu · Aviral Kumar · Yevgen Chebotar · Karol Hausman · Sergey Levine · Chelsea Finn -
2021 Poster: Meta-learning with an Adaptive Task Scheduler »
Huaxiu Yao · Yu Wang · Ying Wei · Peilin Zhao · Mehrdad Mahdavi · Defu Lian · Chelsea Finn -
2021 Poster: Pay Attention to MLPs »
Hanxiao Liu · Zihang Dai · David So · Quoc V Le -
2021 : Diamond: A MineRL Competition on Training Sample-Efficient Agents + Q&A »
William Guss · Alara Dirik · Byron Galbraith · Brandon Houghton · Anssi Kanervisto · Noboru Kuno · Stephanie Milani · Sharada Mohanty · Karolis Ramanauskas · Ruslan Salakhutdinov · Rohin Shah · Nicholay Topin · Steven Wang · Cody Wild -
2021 Poster: Noether Networks: meta-learning useful conserved quantities »
Ferran Alet · Dylan Doblar · Allan Zhou · Josh Tenenbaum · Kenji Kawaguchi · Chelsea Finn -
2021 Poster: MAUVE: Measuring the Gap Between Neural Text and Human Text using Divergence Frontiers »
Krishna Pillutla · Swabha Swayamdipta · Rowan Zellers · John Thickstun · Sean Welleck · Yejin Choi · Zaid Harchaoui -
2021 Poster: MarioNette: Self-Supervised Sprite Learning »
Dmitriy Smirnov · MICHAEL GHARBI · Matthew Fisher · Vitor Guizilini · Alexei Efros · Justin Solomon -
2021 Poster: Differentiable Annealed Importance Sampling and the Perils of Gradient Noise »
Guodong Zhang · Kyle Hsu · Jianing Li · Chelsea Finn · Roger Grosse -
2021 Poster: Autonomous Reinforcement Learning via Subgoal Curricula »
Archit Sharma · Abhishek Gupta · Sergey Levine · Karol Hausman · Chelsea Finn -
2021 Poster: Adaptive Risk Minimization: Learning to Adapt to Domain Shift »
Marvin Zhang · Henrik Marklund · Nikita Dhawan · Abhishek Gupta · Sergey Levine · Chelsea Finn -
2021 : CommonsenseQA 2.0: Exposing the Limits of AI through Gamification »
Alon Talmor · Ori Yoran · Ronan Le Bras · Chandra Bhagavatula · Yoav Goldberg · Yejin Choi · Jonathan Berant -
2021 Oral: MAUVE: Measuring the Gap Between Neural Text and Human Text using Divergence Frontiers »
Krishna Pillutla · Swabha Swayamdipta · Rowan Zellers · John Thickstun · Sean Welleck · Yejin Choi · Zaid Harchaoui -
2020 : QA: Chelsea Finn »
Chelsea Finn -
2020 : Mini-panel discussion 3 - Prioritizing Real World RL Challenges »
Chelsea Finn · Thomas Dietterich · Angela Schoellig · Anca Dragan · Anusha Nagabandi · Doina Precup -
2020 : Invited Talk: Chelsea Finn »
Chelsea Finn -
2020 : Keynote: Chelsea Finn »
Chelsea Finn -
2020 : Q & A and Panel Session with Dan Weld, Kristen Grauman, Scott Yih, Emma Brunskill, and Alex Ratner »
Kristen Grauman · Wen-tau Yih · Alexander Ratner · Emma Brunskill · Douwe Kiela · Daniel S. Weld -
2020 : QA: Kristen Grauman »
Kristen Grauman -
2020 : Invited Talk: Kristen Grauman »
Kristen Grauman -
2020 : QA: Yann LeCun »
Yann LeCun -
2020 : Invited Talk: Yann LeCun »
Yann LeCun -
2020 : QA: Alexei Efros »
Alexei Efros -
2020 : Invited Talk: Alexei Efros »
Alexei Efros -
2020 : QA: Yejin Choi »
Yejin Choi -
2020 : Invited Talk: Yejin Choi »
Yejin Choi -
2020 : QA: Ruslan Salakhutdinov »
Ruslan Salakhutdinov -
2020 : Invited Talk: Ruslan Salakhutdinov »
Ruslan Salakhutdinov -
2020 Workshop: Self-Supervised Learning -- Theory and Practice »
Pengtao Xie · Shanghang Zhang · Pulkit Agrawal · Ishan Misra · Cynthia Rudin · Abdelrahman Mohamed · Wenzhen Yuan · Barret Zoph · Laurens van der Maaten · Xingyi Yang · Eric Xing -
2020 : Invited talk - Underfitting and Uncertainty in Self-Supervised Predictive Models »
Chelsea Finn -
2020 Workshop: Deep Reinforcement Learning »
Pieter Abbeel · Chelsea Finn · Joelle Pineau · David Silver · Satinder Singh · Coline Devin · Misha Laskin · Kimin Lee · Janarthanan Rajendran · Vivek Veeriah -
2020 : Adversarial, Socially Aware, and Commonsensical Data »
Yejin Choi -
2020 Poster: Weakly-Supervised Reinforcement Learning for Controllable Behavior »
Lisa Lee · Benjamin Eysenbach · Russ Salakhutdinov · Shixiang (Shane) Gu · Chelsea Finn -
2020 Poster: Evolving Normalization-Activation Layers »
Hanxiao Liu · Andy Brock · Karen Simonyan · Quoc V Le -
2020 Spotlight: Evolving Normalization-Activation Layers »
Hanxiao Liu · Andy Brock · Karen Simonyan · Quoc V Le -
2020 Poster: Continual Learning of Control Primitives : Skill Discovery via Reset-Games »
Kelvin Xu · Siddharth Verma · Chelsea Finn · Sergey Levine -
2020 Poster: Gradient Surgery for Multi-Task Learning »
Tianhe Yu · Saurabh Kumar · Abhishek Gupta · Sergey Levine · Karol Hausman · Chelsea Finn -
2020 Poster: PyGlove: Symbolic Programming for Automated Machine Learning »
Daiyi Peng · Xuanyi Dong · Esteban Real · Mingxing Tan · Yifeng Lu · Gabriel Bender · Hanxiao Liu · Adam Kraft · Chen Liang · Quoc V Le -
2020 Poster: RandAugment: Practical Automated Data Augmentation with a Reduced Search Space »
Ekin Dogus Cubuk · Barret Zoph · Jonathon Shlens · Quoc V Le -
2020 Oral: PyGlove: Symbolic Programming for Automated Machine Learning »
Daiyi Peng · Xuanyi Dong · Esteban Real · Mingxing Tan · Yifeng Lu · Gabriel Bender · Hanxiao Liu · Adam Kraft · Chen Liang · Quoc V Le -
2020 Poster: Regularizing Black-box Models for Improved Interpretability »
Gregory Plumb · Maruan Al-Shedivat · Ángel Alexander Cabrera · Adam Perer · Eric Xing · Ameet Talwalkar -
2020 Poster: AutoSync: Learning to Synchronize for Data-Parallel Distributed Deep Learning »
Hao Zhang · Yuan Li · Zhijie Deng · Xiaodan Liang · Lawrence Carin · Eric Xing -
2020 Poster: Continuous Meta-Learning without Tasks »
James Harrison · Apoorva Sharma · Chelsea Finn · Marco Pavone -
2020 Poster: Improving GAN Training with Probability Ratio Clipping and Sample Reweighting »
Yue Wu · Pan Zhou · Andrew Wilson · Eric Xing · Zhiting Hu -
2020 Poster: Space-Time Correspondence as a Contrastive Random Walk »
Allan Jabri · Andrew Owens · Alexei Efros -
2020 Poster: Learning Affordance Landscapes for Interaction Exploration in 3D Environments »
Tushar Nagarajan · Kristen Grauman -
2020 Poster: Rethinking Pre-training and Self-training »
Barret Zoph · Golnaz Ghiasi · Tsung-Yi Lin · Yin Cui · Hanxiao Liu · Ekin Dogus Cubuk · Quoc V Le -
2020 Spotlight: Learning Affordance Landscapes for Interaction Exploration in 3D Environments »
Tushar Nagarajan · Kristen Grauman -
2020 Oral: Rethinking Pre-training and Self-training »
Barret Zoph · Golnaz Ghiasi · Tsung-Yi Lin · Yin Cui · Hanxiao Liu · Ekin Dogus Cubuk · Quoc V Le -
2020 Oral: Space-Time Correspondence as a Contrastive Random Walk »
Allan Jabri · Andrew Owens · Alexei Efros -
2020 Poster: One Solution is Not All You Need: Few-Shot Extrapolation via Structured MaxEnt RL »
Saurabh Kumar · Aviral Kumar · Sergey Levine · Chelsea Finn -
2020 Poster: Long-Horizon Visual Planning with Goal-Conditioned Hierarchical Predictors »
Karl Pertsch · Oleh Rybkin · Frederik Ebert · Shenghao Zhou · Dinesh Jayaraman · Chelsea Finn · Sergey Levine -
2020 Poster: Swapping Autoencoder for Deep Image Manipulation »
Taesung Park · Jun-Yan Zhu · Oliver Wang · Jingwan Lu · Eli Shechtman · Alexei Efros · Richard Zhang -
2020 Poster: Unsupervised Data Augmentation for Consistency Training »
Qizhe Xie · Zihang Dai · Eduard Hovy · Thang Luong · Quoc V Le -
2020 Poster: MOPO: Model-based Offline Policy Optimization »
Tianhe Yu · Garrett Thomas · Lantao Yu · Stefano Ermon · James Zou · Sergey Levine · Chelsea Finn · Tengyu Ma -
2020 Poster: Funnel-Transformer: Filtering out Sequential Redundancy for Efficient Language Processing »
Zihang Dai · Guokun Lai · Yiming Yang · Quoc V Le -
2019 : Contributed Session - Spotlight Talks »
Jonathan Frankle · David Schwab · Ari Morcos · Qianli Ma · Yao-Hung Hubert Tsai · Ruslan Salakhutdinov · YiDing Jiang · Dilip Krishnan · Hossein Mobahi · Samy Bengio · Sho Yaida · Muqiao Yang -
2019 : Poster Presentations »
Rahul Mehta · Andrew Lampinen · Binghong Chen · Sergio Pascual-Diaz · Jordi Grau-Moya · Aldo Faisal · Jonathan Tompson · Yiren Lu · Khimya Khetarpal · Martin Klissarov · Pierre-Luc Bacon · Doina Precup · Thanard Kurutach · Aviv Tamar · Pieter Abbeel · Jinke He · Maximilian Igl · Shimon Whiteson · Wendelin Boehmer · Raphaël Marinier · Olivier Pietquin · Karol Hausman · Sergey Levine · Chelsea Finn · Tianhe Yu · Lisa Lee · Benjamin Eysenbach · Emilio Parisotto · Eric Xing · Ruslan Salakhutdinov · Hongyu Ren · Anima Anandkumar · Deepak Pathak · Christopher Lu · Trevor Darrell · Alexei Efros · Phillip Isola · Feng Liu · Bo Han · Gang Niu · Masashi Sugiyama · Saurabh Kumar · Janith Petangoda · Johan Ferret · James McClelland · Kara Liu · Animesh Garg · Robert Lange -
2019 : Oral Presentations »
Janith Petangoda · Sergio Pascual-Diaz · Jordi Grau-Moya · Raphaël Marinier · Olivier Pietquin · Alexei Efros · Phillip Isola · Trevor Darrell · Christopher Lu · Deepak Pathak · Johan Ferret -
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 Choe · Henning Petzka · Ashish Verma · Zhichao Lin · Cristian Sminchisescu -
2019 : Opening Remarks »
Manzil Zaheer · Nicholas Monath · Ari Kobren · Junier Oliva · Barnabas Poczos · Ruslan Salakhutdinov · Andrew McCallum -
2019 Workshop: Sets and Partitions »
Nicholas Monath · Manzil Zaheer · Andrew McCallum · Ari Kobren · Junier Oliva · Barnabas Poczos · Ruslan Salakhutdinov -
2019 : Invited Talk (Yejin Choi) »
Yejin Choi -
2019 : Yejin Choi »
Yejin Choi -
2019 Workshop: Learning with Rich Experience: Integration of Learning Paradigms »
Zhiting Hu · Andrew Wilson · Chelsea Finn · Lisa Lee · Taylor Berg-Kirkpatrick · Ruslan Salakhutdinov · Eric Xing -
2019 : TBD »
Yann LeCun -
2019 Poster: XLNet: Generalized Autoregressive Pretraining for Language Understanding »
Zhilin Yang · Zihang Dai · Yiming Yang · Jaime Carbonell · Russ Salakhutdinov · Quoc V Le -
2019 Poster: Defending Against Neural Fake News »
Rowan Zellers · Ari Holtzman · Hannah Rashkin · Yonatan Bisk · Ali Farhadi · Franziska Roesner · Yejin Choi -
2019 Oral: XLNet: Generalized Autoregressive Pretraining for Language Understanding »
Zhilin Yang · Zihang Dai · Yiming Yang · Jaime Carbonell · Russ Salakhutdinov · Quoc V Le -
2019 Poster: CondConv: Conditionally Parameterized Convolutions for Efficient Inference »
Brandon Yang · Gabriel Bender · Quoc V Le · Jiquan Ngiam -
2019 Poster: Learning Robust Global Representations by Penalizing Local Predictive Power »
Haohan Wang · Songwei Ge · Zachary Lipton · Eric Xing -
2019 Poster: Learning Data Manipulation for Augmentation and Weighting »
Zhiting Hu · Bowen Tan · Russ Salakhutdinov · Tom Mitchell · Eric Xing -
2019 Poster: Learning Sample-Specific Models with Low-Rank Personalized Regression »
Ben Lengerich · Bryon Aragam · Eric Xing -
2019 Poster: Mixtape: Breaking the Softmax Bottleneck Efficiently »
Zhilin Yang · Thang Luong · Russ Salakhutdinov · Quoc V Le -
2019 Poster: Saccader: Improving Accuracy of Hard Attention Models for Vision »
Gamaleldin Elsayed · Simon Kornblith · Quoc V Le -
2019 Poster: Language as an Abstraction for Hierarchical Deep Reinforcement Learning »
YiDing Jiang · Shixiang (Shane) Gu · Kevin Murphy · Chelsea Finn -
2019 Poster: GPipe: Efficient Training of Giant Neural Networks using Pipeline Parallelism »
Yanping Huang · Youlong Cheng · Ankur Bapna · Orhan Firat · Dehao Chen · Mia Chen · HyoukJoong Lee · Jiquan Ngiam · Quoc V Le · Yonghui Wu · zhifeng Chen -
2019 Poster: Learning to Control Self-Assembling Morphologies: A Study of Generalization via Modularity »
Deepak Pathak · Christopher Lu · Trevor Darrell · Phillip Isola · Alexei Efros -
2019 Spotlight: Learning to Control Self-Assembling Morphologies: A Study of Generalization via Modularity »
Deepak Pathak · Christopher Lu · Trevor Darrell · Phillip Isola · Alexei Efros -
2019 Poster: High Fidelity Video Prediction with Large Stochastic Recurrent Neural Networks »
Ruben Villegas · Arkanath Pathak · Harini Kannan · Dumitru Erhan · Quoc V Le · Honglak Lee -
2018 Poster: The Sample Complexity of Semi-Supervised Learning with Nonparametric Mixture Models »
Chen Dan · Liu Leqi · Bryon Aragam · Pradeep Ravikumar · Eric Xing -
2018 Poster: Symbolic Graph Reasoning Meets Convolutions »
Xiaodan Liang · Zhiting Hu · Hao Zhang · Liang Lin · Eric Xing -
2018 Poster: DAGs with NO TEARS: Continuous Optimization for Structure Learning »
Xun Zheng · Bryon Aragam · Pradeep Ravikumar · Eric Xing -
2018 Poster: Memory Augmented Policy Optimization for Program Synthesis and Semantic Parsing »
Chen Liang · Mohammad Norouzi · Jonathan Berant · Quoc V Le · Ni Lao -
2018 Spotlight: DAGs with NO TEARS: Continuous Optimization for Structure Learning »
Xun Zheng · Bryon Aragam · Pradeep Ravikumar · Eric Xing -
2018 Spotlight: Memory Augmented Policy Optimization for Program Synthesis and Semantic Parsing »
Chen Liang · Mohammad Norouzi · Jonathan Berant · Quoc V Le · Ni Lao -
2018 Poster: Learning Pipelines with Limited Data and Domain Knowledge: A Study in Parsing Physics Problems »
Mrinmaya Sachan · Kumar Avinava Dubey · Tom Mitchell · Dan Roth · Eric Xing -
2018 Poster: Deep Generative Models with Learnable Knowledge Constraints »
Zhiting Hu · Zichao Yang · Russ Salakhutdinov · LIANHUI Qin · Xiaodan Liang · Haoye Dong · Eric Xing -
2018 Poster: DropBlock: A regularization method for convolutional networks »
Golnaz Ghiasi · Tsung-Yi Lin · Quoc V Le -
2018 Poster: Hybrid Retrieval-Generation Reinforced Agent for Medical Image Report Generation »
Yuan Li · Xiaodan Liang · Zhiting Hu · Eric Xing -
2018 Poster: Neural Architecture Search with Bayesian Optimisation and Optimal Transport »
Kirthevasan Kandasamy · Willie Neiswanger · Jeff Schneider · Barnabas Poczos · Eric Xing -
2018 Spotlight: Neural Architecture Search with Bayesian Optimisation and Optimal Transport »
Kirthevasan Kandasamy · Willie Neiswanger · Jeff Schneider · Barnabas Poczos · Eric Xing -
2018 Poster: Unsupervised Text Style Transfer using Language Models as Discriminators »
Zichao Yang · Zhiting Hu · Chris Dyer · Eric Xing · Taylor Berg-Kirkpatrick -
2017 : Panel Session »
Neil Lawrence · Finale Doshi-Velez · Zoubin Ghahramani · Yann LeCun · Max Welling · Yee Whye Teh · Ole Winther -
2017 : Deep Kernel Learning »
Ruslan Salakhutdinov -
2017 : How to stop worrying and learn to love Nearest Neighbors »
Alexei Efros -
2017 Symposium: Metalearning »
Risto Miikkulainen · Quoc V Le · Kenneth Stanley · Chrisantha Fernando -
2017 Oral: Deep Sets »
Manzil Zaheer · Satwik Kottur · Siamak Ravanbakhsh · Barnabas Poczos · Ruslan Salakhutdinov · Alexander Smola -
2017 Poster: Deep Sets »
Manzil Zaheer · Satwik Kottur · Siamak Ravanbakhsh · Barnabas Poczos · Ruslan Salakhutdinov · Alexander Smola -
2017 Poster: Structured Generative Adversarial Networks »
Zhijie Deng · Hao Zhang · Xiaodan Liang · Luona Yang · Shizhen Xu · Jun Zhu · Eric Xing -
2017 Poster: Good Semi-supervised Learning That Requires a Bad GAN »
Zihang Dai · Zhilin Yang · Fan Yang · William Cohen · Ruslan Salakhutdinov -
2017 Poster: Learning Spherical Convolution for Fast Features from 360° Imagery »
Yu-Chuan Su · Kristen Grauman -
2017 Poster: Toward Multimodal Image-to-Image Translation »
Jun-Yan Zhu · Richard Zhang · Deepak Pathak · Trevor Darrell · Alexei Efros · Oliver Wang · Eli Shechtman -
2017 Tutorial: Geometric Deep Learning on Graphs and Manifolds »
Michael Bronstein · Joan Bruna · arthur szlam · Xavier Bresson · Yann LeCun -
2016 : What makes ImageNet good for Transfer Learning? »
Jacob MY Huh · Pulkit Agrawal · Alexei Efros -
2016 : Discussion panel »
Ian Goodfellow · Soumith Chintala · Arthur Gretton · Sebastian Nowozin · Aaron Courville · Yann LeCun · Emily Denton -
2016 : Energy-Based Adversarial Training and Video Prediction »
Yann LeCun -
2016 : Eric Xing »
Eric Xing -
2016 Symposium: Deep Learning Symposium »
Yoshua Bengio · Yann LeCun · Navdeep Jaitly · Roger Grosse -
2016 Poster: Variance Reduction in Stochastic Gradient Langevin Dynamics »
Kumar Avinava Dubey · Sashank J. Reddi · Sinead Williamson · Barnabas Poczos · Alexander Smola · Eric Xing -
2016 Poster: An Online Sequence-to-Sequence Model Using Partial Conditioning »
Navdeep Jaitly · Quoc V Le · Oriol Vinyals · Ilya Sutskever · David Sussillo · Samy Bengio -
2016 Poster: Learning HMMs with Nonparametric Emissions via Spectral Decompositions of Continuous Matrices »
Kirthevasan Kandasamy · Maruan Al-Shedivat · Eric Xing -
2016 Poster: Stochastic Variational Deep Kernel Learning »
Andrew Wilson · Zhiting Hu · Russ Salakhutdinov · Eric Xing -
2015 Workshop: Nonparametric Methods for Large Scale Representation Learning »
Andrew G Wilson · Alexander Smola · Eric Xing -
2015 Poster: Learning to Linearize Under Uncertainty »
Ross Goroshin · Michael Mathieu · Yann LeCun -
2015 Poster: Semi-supervised Sequence Learning »
Andrew Dai · Quoc V Le -
2015 Poster: Character-level Convolutional Networks for Text Classification »
Xiang Zhang · Junbo (Jake) Zhao · Yann LeCun -
2015 Poster: The Human Kernel »
Andrew Wilson · Christoph Dann · Chris Lucas · Eric Xing -
2015 Poster: Deep learning with Elastic Averaging SGD »
Sixin Zhang · Anna Choromanska · Yann LeCun -
2015 Spotlight: The Human Kernel »
Andrew Wilson · Christoph Dann · Chris Lucas · Eric Xing -
2015 Spotlight: Deep learning with Elastic Averaging SGD »
Sixin Zhang · Anna Choromanska · Yann LeCun -
2015 Tutorial: Deep Learning »
Geoffrey E Hinton · Yoshua Bengio · Yann LeCun -
2014 Workshop: Modern Nonparametrics 3: Automating the Learning Pipeline »
Eric Xing · Mladen Kolar · Arthur Gretton · Samory Kpotufe · Han Liu · Zoltán Szabó · Alan Yuille · Andrew G Wilson · Ryan Tibshirani · Sasha Rakhlin · Damian Kozbur · Bharath Sriperumbudur · David Lopez-Paz · Kirthevasan Kandasamy · Francesco Orabona · Andreas Damianou · Wacha Bounliphone · Yanshuai Cao · Arijit Das · Yingzhen Yang · Giulia DeSalvo · Dmitry Storcheus · Roberto Valerio -
2014 Workshop: Modern Machine Learning and Natural Language Processing »
Ankur P Parikh · Avneesh Saluja · Chris Dyer · Eric Xing -
2014 Poster: On Model Parallelization and Scheduling Strategies for Distributed Machine Learning »
Seunghak Lee · Jin Kyu Kim · Xun Zheng · Qirong Ho · Garth Gibson · Eric Xing -
2014 Poster: Sequence to Sequence Learning with Neural Networks »
Ilya Sutskever · Oriol Vinyals · Quoc V Le -
2014 Poster: Diverse Sequential Subset Selection for Supervised Video Summarization »
Boqing Gong · Wei-Lun Chao · Kristen Grauman · Fei Sha -
2014 Oral: Sequence to Sequence Learning with Neural Networks »
Ilya Sutskever · Oriol Vinyals · Quoc V Le -
2014 Poster: Dependent nonparametric trees for dynamic hierarchical clustering »
Kumar Avinava Dubey · Qirong Ho · Sinead Williamson · Eric Xing -
2014 Poster: Predicting Useful Neighborhoods for Lazy Local Learning »
Aron Yu · Kristen Grauman -
2014 Poster: Zero-shot recognition with unreliable attributes »
Dinesh Jayaraman · Kristen Grauman -
2013 Workshop: Randomized Methods for Machine Learning »
David Lopez-Paz · Quoc V Le · Alexander Smola -
2013 Poster: Reshaping Visual Datasets for Domain Adaptation »
Boqing Gong · Kristen Grauman · Fei Sha -
2013 Poster: More Effective Distributed ML via a Stale Synchronous Parallel Parameter Server »
Qirong Ho · James Cipar · Henggang Cui · Seunghak Lee · Jin Kyu Kim · Phillip B. Gibbons · Garth Gibson · Greg Ganger · Eric Xing -
2013 Oral: More Effective Distributed ML via a Stale Synchronous Parallel Parameter Server »
Qirong Ho · James Cipar · Henggang Cui · Seunghak Lee · Jin Kyu Kim · Phillip B. Gibbons · Garth Gibson · Greg Ganger · Eric Xing -
2013 Poster: Variance Reduction for Stochastic Gradient Optimization »
Chong Wang · Xi Chen · Alexander Smola · Eric Xing -
2013 Poster: Restricting exchangeable nonparametric distributions »
Sinead Williamson · Steven MacEachern · Eric Xing -
2013 Spotlight: Restricting exchangeable nonparametric distributions »
Sinead Williamson · Steven MacEachern · Eric Xing -
2013 Poster: A Scalable Approach to Probabilistic Latent Space Inference of Large-Scale Networks »
Junming Yin · Qirong Ho · Eric Xing -
2012 Workshop: Spectral Algorithms for Latent Variable Models »
Ankur P Parikh · Le Song · Eric Xing -
2012 Poster: Monte Carlo Methods for Maximum Margin Supervised Topic Models »
Qixia Jiang · Jun Zhu · Maosong Sun · Eric Xing -
2012 Poster: On Triangular versus Edge Representations --- Towards Scalable Modeling of Networks »
Qirong Ho · Junming Yin · Eric Xing -
2012 Poster: Symmetric Correspondence Topic Models for Multilingual Text Analysis »
Kosuke Fukumasu · Koji Eguchi · Eric Xing -
2012 Spotlight: Symmetric Correspondence Topic Models for Multilingual Text Analysis »
Kosuke Fukumasu · Koji Eguchi · Eric Xing -
2012 Poster: Semantic Kernel Forests from Multiple Taxonomies »
Sung Ju Hwang · Kristen Grauman · Fei Sha -
2011 Poster: Learning a Tree of Metrics with Disjoint Visual Features »
Sung Ju Hwang · Kristen Grauman · Fei Sha -
2011 Poster: Infinite Latent SVM for Classification and Multi-task Learning »
Jun Zhu · Ning Chen · Eric Xing -
2011 Poster: Kernel Embeddings of Latent Tree Graphical Models »
Le Song · Ankur P Parikh · Eric Xing -
2011 Poster: Large-Scale Category Structure Aware Image Categorization »
Bin Zhao · Li Fei-Fei · Eric Xing -
2010 Poster: Large Margin Learning of Upstream Scene Understanding Models »
Jun Zhu · Li-Jia Li · Li Fei-Fei · Eric Xing -
2010 Poster: Predictive Subspace Learning for Multi-view Data: a Large Margin Approach »
Ning Chen · Jun Zhu · Eric Xing -
2010 Poster: Hashing Hyperplane Queries to Near Points with Applications to Large-Scale Active Learning »
Prateek Jain · Sudheendra Vijayanarasimhan · Kristen Grauman -
2010 Poster: Object Bank: A High-Level Image Representation for Scene Classification & Semantic Feature Sparsification »
Li-Jia Li · Hao Su · Eric Xing · Li Fei-Fei -
2010 Poster: Adaptive Multi-Task Lasso: with Application to eQTL Detection »
Seunghak Lee · Jun Zhu · Eric Xing -
2009 Poster: Heterogeneous multitask learning with joint sparsity constraints »
Xiaolin Yang · Seyoung Kim · Eric Xing -
2009 Poster: Time-Varying Dynamic Bayesian Networks »
Le Song · Mladen Kolar · Eric Xing -
2009 Spotlight: Time-Varying Dynamic Bayesian Networks »
Le Song · Mladen Kolar · Eric Xing -
2009 Poster: Sparsistent Learning of Varying-coefficient Models with Structural Changes »
Mladen Kolar · Le Song · Eric Xing -
2009 Spotlight: Sparsistent Learning of Varying-coefficient Models with Structural Changes »
Mladen Kolar · Le Song · Eric Xing -
2008 Workshop: Analyzing Graphs: Theory and Applications »
Edo M Airoldi · David Blei · Jake M Hofman · Tony Jebara · Eric Xing -
2008 Oral: Multi-Level Active Prediction of Useful Image Annotations for Recognition »
Sudheendra N Vijayanarasimhan · Kristen Grauman -
2008 Poster: Mixed Membership Stochastic Blockmodels »
Edo M Airoldi · David Blei · Stephen E Fienberg · Eric Xing -
2008 Poster: Multi-Level Active Prediction of Useful Image Annotations for Recognition »
Sudheendra N Vijayanarasimhan · Kristen Grauman -
2008 Spotlight: Mixed Membership Stochastic Blockmodels »
Edo M Airoldi · David Blei · Stephen E Fienberg · Eric Xing -
2008 Poster: Online Metric Learning and Fast Similarity Search »
Prateek Jain · Brian Kulis · Inderjit Dhillon · Kristen Grauman -
2008 Poster: Partially Observed Maximum Entropy Discrimination Markov Networks »
Jun Zhu · Eric Xing · Bo Zhang -
2008 Oral: Online Metric Learning and Fast Similarity Search »
Prateek Jain · Brian Kulis · Inderjit Dhillon · Kristen Grauman -
2007 Workshop: Statistical Network Models »
Kevin Murphy · Lise Getoor · Eric Xing · Raphael Gottardo -
2007 Poster: HM-BiTAM: Bilingual Topic Exploration, Word Alignment, and Translation »
Bing Zhao · Eric Xing -
2006 Poster: A Hidden Markov Dirichlet Process Model for Genetic Recombination in Open Ancestral Space »
KyungAh Sohn · Eric Xing -
2006 Poster: Approximate Correspondences in High Dimensions »
Kristen Grauman · Trevor Darrell -
2006 Spotlight: Approximate Correspondences in High Dimensions »
Kristen Grauman · Trevor Darrell -
2006 Talk: A Hidden Markov Dirichlet Process Model for Genetic Recombination in Open Ancestral Space »
KyungAh Sohn · Eric Xing