Timezone: »
We consider unsupervised domain adaptation (UDA), where labeled data from a source domain (e.g., photos) and unlabeled data from a target domain (e.g., sketches) are used to learn a classifier for the target domain. Conventional UDA methods (e.g., domain adversarial training) learn domain-invariant features to generalize from the source domain to the target domain. In this paper, we show that contrastive pre-training, which learns features on unlabeled source and target data and then fine-tunes on labeled source data, is competitive with strong UDA methods. However, we find that contrastive pre-training does not learn domain-invariant features, diverging from conventional UDA intuitions. We show theoretically that contrastive pre-training can learn features that vary subtantially across domains but still generalize to the target domain, by disentangling domain and class information. We empirically validate our theory on benchmark vision datasets.
Author Information
Kendrick Shen (Stanford University)
Robbie Jones (Stanford University)
Ananya Kumar (Stanford University)
Sang Michael Xie (Stanford University)
Jeff Z. HaoChen (Stanford University)
Tengyu Ma (Stanford University)
Percy Liang (Stanford University)
Related Events (a corresponding poster, oral, or spotlight)
-
2022 Poster: Connect, Not Collapse: Explaining Contrastive Learning for Unsupervised Domain Adaptation »
Thu. Jul 21st through Fri the 22nd Room Hall E #317
More from the Same Authors
-
2021 : Provable Model-based Nonlinear Bandit and Reinforcement Learning: Shelve Optimism, Embrace Virtual Curvature »
Kefan Dong · Jiaqi Yang · Tengyu Ma -
2022 : LinkBERT: Language Model Pretraining with Document Link Knowledge »
Michihiro Yasunaga · Jure Leskovec · Percy Liang -
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 : Panel Discussion »
Megan Ansdell · Nathan Lambert · Ludwig Schmidt · Praveen Paritosh · Sang Michael Xie -
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 Oral: Same Pre-training Loss, Better Downstream: Implicit Bias Matters for Language Models »
Hong Liu · Sang Michael Xie · Zhiyuan Li · Tengyu Ma -
2023 Poster: Same Pre-training Loss, Better Downstream: Implicit Bias Matters for Language Models »
Hong Liu · Sang Michael Xie · Zhiyuan Li · Tengyu Ma -
2023 Poster: Whose Opinions Do Language Models Reflect? »
Shibani Santurkar · Esin Durmus · Faisal Ladhak · Cinoo Lee · Percy Liang · Tatsunori Hashimoto -
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 : Discussion Panel »
Percy Liang · Léon Bottou · Jayashree Kalpathy-Cramer · Alex Smola -
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 -
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 : 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 -
2018 Poster: On the Relationship between Data Efficiency and Error for Uncertainty Sampling »
Stephen Mussmann · Percy Liang -
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 -
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 Poster: Developing Bug-Free Machine Learning Systems With Formal Mathematics »
Daniel Selsam · Percy Liang · David L Dill -
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 Talk: Convexified Convolutional Neural Networks »
Yuchen Zhang · Percy Liang · Martin Wainwright -
2017 Talk: Understanding Black-box Predictions via Influence Functions »
Pang Wei Koh · Percy Liang