More from the Same Authors

• 2021 : Multimodal AutoML on Structured Tables with Text Fields »
  Xingjian Shi · Jonas Mueller · Nick Erickson · Mu Li · Alex Smola
• 2021 : Evaluating subgroup disparity using epistemic for breast density assessment in mammography »
  charlie lu · Andreanne Lemay · Katharina Hoebel · Jayashree Kalpathy-Cramer
• 2021 : Continuous Doubly Constrained Batch Reinforcement Learning »
  Rasool Fakoor · Jonas Mueller · Kavosh Asadi · Pratik Chaudhari · Alex Smola
• 2022 : LinkBERT: Language Model Pretraining with Document Link Knowledge »
  Michihiro Yasunaga · Jure Leskovec · Percy Liang
• 2022 : Adaptive Interest for Emphatic Reinforcement Learning »
  Martin Klissarov · Rasool Fakoor · Jonas Mueller · Kavosh Asadi · Taesup Kim · Alex Smola
• 2022 : Estimating Test Performance for AI Medical Devices under Distribution Shift with Conformal Prediction »
  charlie lu · Syed Rakin Ahmed · Praveer Singh · Jayashree Kalpathy-Cramer
• 2023 : 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 Le · Tengyu Ma · Adams Wei Yu
• 2023 : Retrieval-Augmented Multimodal Language Modeling »
  Michihiro Yasunaga · Armen Aghajanyan · Weijia Shi · Rich James · Jure Leskovec · Percy Liang · Mike Lewis · Luke Zettlemoyer · Wen-tau Yih
• 2023 : Lexinvariant Language Models »
  Qian Huang · Eric Zelikman · Sarah Chen · Yuhuai Wu · Greg Valiant · Percy Liang
• 2023 : PRODIGY: Enabling In-context Learning Over Graphs »
  Qian Huang · Hongyu Ren · Peng Chen · Gregor Kržmanc · Daniel Zeng · Percy Liang · Jure Leskovec
• 2023 : Sophia: A Scalable Stochastic Second-order Optimizer for Language Model Pre-training »
  Hong Liu · Zhiyuan Li · David Hall · Percy Liang · Tengyu Ma
• 2023 Workshop: ES-FoMo: Efficient Systems for Foundation Models »
  Julien Launay · Daniel Y Fu · Tri Dao · Daniel Hesslow · Beidi Chen · Azalia Mirhoseini · Percy Liang
• 2023 Poster: Whose Opinions Do Language Models Reflect? »
  Shibani Santurkar · Esin Durmus · Faisal Ladhak · Cinoo Lee · Percy Liang · Tatsunori Hashimoto
• 2023 Poster: RLSbench: Domain Adaptation Under Relaxed Label Shift »
  Saurabh Garg · Nick Erickson · University of California James Sharpnack · Alex Smola · Sivaraman Balakrishnan · Zachary Lipton
• 2023 Poster: FlexGen: High-Throughput Generative Inference of Large Language Models with a Single GPU »
  Ying Sheng · Lianmin Zheng · Binhang Yuan · Zhuohan Li · Max Ryabinin · Beidi Chen · Percy Liang · Christopher Re · Ion Stoica · Ce Zhang
• 2023 Oral: FlexGen: High-Throughput Generative Inference of Large Language Models with a Single GPU »
  Ying Sheng · Lianmin Zheng · Binhang Yuan · Zhuohan Li · Max Ryabinin · Beidi Chen · Percy Liang · Christopher Re · Ion Stoica · Ce Zhang
• 2023 Oral: Whose Opinions Do Language Models Reflect? »
  Shibani Santurkar · Esin Durmus · Faisal Ladhak · Cinoo Lee · Percy Liang · Tatsunori Hashimoto
• 2023 Oral: Evaluating Self-Supervised Learning via Risk Decomposition »
  Yann Dubois · Tatsunori Hashimoto · Percy Liang
• 2023 Poster: Evaluating Self-Supervised Learning via Risk Decomposition »
  Yann Dubois · Tatsunori Hashimoto · Percy Liang
• 2023 Poster: CocktailSGD: Fine-tuning Foundation Models over 500Mbps Networks »
  Jue Wang · Yucheng Lu · Binhang Yuan · Beidi Chen · Percy Liang · Chris De Sa · Christopher Re · Ce Zhang
• 2023 Poster: Out-of-Domain Robustness via Targeted Augmentations »
  Irena Gao · Shiori Sagawa · Pang Wei Koh · Tatsunori Hashimoto · Percy Liang
• 2023 Poster: One-sided Matrix Completion from Two Observations Per Row »
  Steven Cao · Percy Liang · Greg Valiant
• 2023 Poster: Retrieval-Augmented Multimodal Language Modeling »
  Michihiro Yasunaga · Armen Aghajanyan · Weijia Shi · Richard James · Jure Leskovec · Percy Liang · Mike Lewis · Luke Zettlemoyer · Scott Yih
• 2022 : Distribution Shifts in Healthcare—A Key Barrier to Safe Deployment of Machine Learning Algorithms in the Clinic »
  Jayashree Kalpathy-Cramer
• 2022 Workshop: The First Workshop on Pre-training: Perspectives, Pitfalls, and Paths Forward »
  Huaxiu Yao · Hugo Larochelle · Percy Liang · Colin Raffel · Jian Tang · Ying WEI · Saining Xie · Eric Xing · Chelsea Finn
• 2022 Poster: Rich Feature Construction for the Optimization-Generalization Dilemma »
  Jianyu Zhang · David Lopez-Paz · Léon Bottou
• 2022 Poster: Connect, Not Collapse: Explaining Contrastive Learning for Unsupervised Domain Adaptation »
  Kendrick Shen · Robbie Jones · Ananya Kumar · Sang Michael Xie · Jeff Z. HaoChen · Tengyu Ma · Percy Liang
• 2022 Spotlight: Rich Feature Construction for the Optimization-Generalization Dilemma »
  Jianyu Zhang · David Lopez-Paz · Léon Bottou
• 2022 Oral: Connect, Not Collapse: Explaining Contrastive Learning for Unsupervised Domain Adaptation »
  Kendrick Shen · Robbie Jones · Ananya Kumar · Sang Michael Xie · Jeff Z. HaoChen · Tengyu Ma · Percy Liang
• 2022 Poster: Partial and Asymmetric Contrastive Learning for Out-of-Distribution Detection in Long-Tailed Recognition »
  Haotao Wang · Aston Zhang · Yi Zhu · Shuai Zheng · Mu Li · Alex Smola · Zhangyang “Atlas” Wang
• 2022 Oral: Partial and Asymmetric Contrastive Learning for Out-of-Distribution Detection in Long-Tailed Recognition »
  Haotao Wang · Aston Zhang · Yi Zhu · Shuai Zheng · Mu Li · Alex Smola · Zhangyang “Atlas” Wang
• 2021 Poster: WILDS: A Benchmark of in-the-Wild Distribution Shifts »
  Pang Wei Koh · Shiori Sagawa · Henrik Marklund · Sang Michael Xie · Marvin Zhang · Akshay Balsubramani · Weihua Hu · Michihiro Yasunaga · Richard Lanas Phillips · Irena Gao · Tony Lee · Etienne David · Ian Stavness · Wei Guo · Berton Earnshaw · Imran Haque · Sara Beery · Jure Leskovec · Anshul Kundaje · Emma Pierson · Sergey Levine · Chelsea Finn · Percy Liang
• 2021 Poster: Composed Fine-Tuning: Freezing Pre-Trained Denoising Autoencoders for Improved Generalization »
  Sang Michael Xie · Tengyu Ma · Percy Liang
• 2021 Oral: WILDS: A Benchmark of in-the-Wild Distribution Shifts »
  Pang Wei Koh · Shiori Sagawa · Henrik Marklund · Sang Michael Xie · Marvin Zhang · Akshay Balsubramani · Weihua Hu · Michihiro Yasunaga · Richard Lanas Phillips · Irena Gao · Tony Lee · Etienne David · Ian Stavness · Wei Guo · Berton Earnshaw · Imran Haque · Sara Beery · Jure Leskovec · Anshul Kundaje · Emma Pierson · Sergey Levine · Chelsea Finn · Percy Liang
• 2021 Oral: Composed Fine-Tuning: Freezing Pre-Trained Denoising Autoencoders for Improved Generalization »
  Sang Michael Xie · Tengyu Ma · Percy Liang
• 2021 Poster: Accuracy on the Line: on the Strong Correlation Between Out-of-Distribution and In-Distribution Generalization »
  John Miller · Rohan Taori · Aditi Raghunathan · Shiori Sagawa · Pang Wei Koh · Vaishaal Shankar · Percy Liang · Yair Carmon · Ludwig Schmidt
• 2021 Poster: Break-It-Fix-It: Unsupervised Learning for Program Repair »
  Michihiro Yasunaga · Percy Liang
• 2021 Oral: Break-It-Fix-It: Unsupervised Learning for Program Repair »
  Michihiro Yasunaga · Percy Liang
• 2021 Spotlight: Accuracy on the Line: on the Strong Correlation Between Out-of-Distribution and In-Distribution Generalization »
  John Miller · Rohan Taori · Aditi Raghunathan · Shiori Sagawa · Pang Wei Koh · Vaishaal Shankar · Percy Liang · Yair Carmon · Ludwig Schmidt
• 2021 Poster: Decoupling Exploration and Exploitation for Meta-Reinforcement Learning without Sacrifices »
  Evan Liu · Aditi Raghunathan · Percy Liang · Chelsea Finn
• 2021 Spotlight: Decoupling Exploration and Exploitation for Meta-Reinforcement Learning without Sacrifices »
  Evan Liu · Aditi Raghunathan · Percy Liang · Chelsea Finn
• 2021 Poster: Catformer: Designing Stable Transformers via Sensitivity Analysis »
  Jared Quincy Davis · Albert Gu · Krzysztof Choromanski · Tri Dao · Christopher Re · Chelsea Finn · Percy Liang
• 2021 Poster: Just Train Twice: Improving Group Robustness without Training Group Information »
  Evan Liu · Behzad Haghgoo · Annie Chen · Aditi Raghunathan · Pang Wei Koh · Shiori Sagawa · Percy Liang · Chelsea Finn
• 2021 Spotlight: Catformer: Designing Stable Transformers via Sensitivity Analysis »
  Jared Quincy Davis · Albert Gu · Krzysztof Choromanski · Tri Dao · Christopher Re · Chelsea Finn · Percy Liang
• 2021 Oral: Just Train Twice: Improving Group Robustness without Training Group Information »
  Evan Liu · Behzad Haghgoo · Annie Chen · Aditi Raghunathan · Pang Wei Koh · Shiori Sagawa · Percy Liang · Chelsea Finn
• 2020 : Panel Discussion »
  Neil Lawrence · Mihaela van der Schaar · Alex Smola · Valerio Perrone · Jack Parker-Holder · Zhengying Liu
• 2020 : "AutoGluon and Distillation" by Alex Smola »
  Alex Smola
• 2020 : Keynote #3 Percy Liang »
  Percy Liang
• 2020 Poster: Concept Bottleneck Models »
  Pang Wei Koh · Thao Nguyen · Yew Siang Tang · Stephen Mussmann · Emma Pierson · Been Kim · Percy Liang
• 2020 Poster: Graph-based, Self-Supervised Program Repair from Diagnostic Feedback »
  Michihiro Yasunaga · Percy Liang
• 2020 Poster: Understanding Self-Training for Gradual Domain Adaptation »
  Ananya Kumar · Tengyu Ma · Percy Liang
• 2020 Poster: Understanding and Mitigating the Tradeoff between Robustness and Accuracy »
  Aditi Raghunathan · Sang Michael Xie · Fanny Yang · John Duchi · Percy Liang
• 2020 Poster: An Investigation of Why Overparameterization Exacerbates Spurious Correlations »
  Shiori Sagawa · aditi raghunathan · Pang Wei Koh · Percy Liang
• 2020 Poster: Robustness to Spurious Correlations via Human Annotations »
  Megha Srivastava · Tatsunori Hashimoto · Percy Liang
• 2020 Poster: Feature Noise Induces Loss Discrepancy Across Groups »
  Fereshte Khani · Percy Liang
• 2019 Workshop: Workshop on the Security and Privacy of Machine Learning »
  Nicolas Papernot · Florian Tramer · Bo Li · Dan Boneh · David Evans · Somesh Jha · Percy Liang · Patrick McDaniel · Jacob Steinhardt · Dawn Song
• 2019 Poster: Deep Factors for Forecasting »
  Yuyang Wang · Alex Smola · Danielle Robinson · Jan Gasthaus · Dean Foster · Tim Januschowski
• 2019 Oral: Deep Factors for Forecasting »
  Yuyang Wang · Alex Smola · Danielle Robinson · Jan Gasthaus · Dean Foster · Tim Januschowski
• 2019 Tutorial: A Tutorial on Attention in Deep Learning »
  Alex Smola · Aston Zhang
• 2018 Poster: On the Relationship between Data Efficiency and Error for Uncertainty Sampling »
  Stephen Mussmann · Percy Liang
• 2018 Poster: Learning Steady-States of Iterative Algorithms over Graphs »
  Hanjun Dai · Zornitsa Kozareva · Bo Dai · Alex Smola · Le Song
• 2018 Poster: Fairness Without Demographics in Repeated Loss Minimization »
  Tatsunori Hashimoto · Megha Srivastava · Hongseok Namkoong · Percy Liang
• 2018 Oral: Fairness Without Demographics in Repeated Loss Minimization »
  Tatsunori Hashimoto · Megha Srivastava · Hongseok Namkoong · Percy Liang
• 2018 Oral: On the Relationship between Data Efficiency and Error for Uncertainty Sampling »
  Stephen Mussmann · Percy Liang
• 2018 Oral: Learning Steady-States of Iterative Algorithms over Graphs »
  Hanjun Dai · Zornitsa Kozareva · Bo Dai · Alex Smola · Le Song
• 2017 Poster: Canopy --- Fast Sampling with Cover Trees »
  Manzil Zaheer · Satwik Kottur · Amr Ahmed · Jose Moura · Alex Smola
• 2017 Poster: World of Bits: An Open-Domain Platform for Web-Based Agents »
  Tim Shi · Andrej Karpathy · Jim Fan · Jonathan Hernandez · Percy Liang
• 2017 Talk: World of Bits: An Open-Domain Platform for Web-Based Agents »
  Tim Shi · Andrej Karpathy · Jim Fan · Jonathan Hernandez · Percy Liang
• 2017 Talk: Canopy --- Fast Sampling with Cover Trees »
  Manzil Zaheer · Satwik Kottur · Amr Ahmed · Jose Moura · Alex Smola
• 2017 Poster: Latent LSTM Allocation: Joint clustering and non-linear dynamic modeling of sequence data »
  Manzil Zaheer · Amr Ahmed · Alex Smola
• 2017 Poster: Developing Bug-Free Machine Learning Systems With Formal Mathematics »
  Daniel Selsam · Percy Liang · David L Dill
• 2017 Talk: Latent LSTM Allocation: Joint clustering and non-linear dynamic modeling of sequence data »
  Manzil Zaheer · Amr Ahmed · Alex Smola
• 2017 Talk: Developing Bug-Free Machine Learning Systems With Formal Mathematics »
  Daniel Selsam · Percy Liang · David L Dill
• 2017 Poster: Convexified Convolutional Neural Networks »
  Yuchen Zhang · Percy Liang · Martin Wainwright
• 2017 Poster: Understanding Black-box Predictions via Influence Functions »
  Pang Wei Koh · Percy Liang
• 2017 Poster: Wasserstein Generative Adversarial Networks »
  Martin Arjovsky · Soumith Chintala · Léon Bottou
• 2017 Talk: Convexified Convolutional Neural Networks »
  Yuchen Zhang · Percy Liang · Martin Wainwright
• 2017 Talk: Wasserstein Generative Adversarial Networks »
  Martin Arjovsky · Soumith Chintala · Léon Bottou
• 2017 Talk: Understanding Black-box Predictions via Influence Functions »
  Pang Wei Koh · Percy Liang
• 2017 Tutorial: Distributed Deep Learning with MxNet Gluon »
  Alex Smola · Aran Khanna