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Discussion Panel
Percy Liang · Léon Bottou · Jayashree Kalpathy-Cramer · Alex Smola
Author Information
Percy Liang (Stanford University)
Léon Bottou (Meta AI)
Jayashree Kalpathy-Cramer (University of Colorado Anchutz Campus)
Alex Smola (Amazon)
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2021 : Multimodal AutoML on Structured Tables with Text Fields »
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2021 : Evaluating subgroup disparity using epistemic for breast density assessment in mammography »
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2021 : Continuous Doubly Constrained Batch Reinforcement Learning »
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2022 : Adaptive Interest for Emphatic Reinforcement Learning »
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2022 : Estimating Test Performance for AI Medical Devices under Distribution Shift with Conformal Prediction »
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2023 : DoReMi: Optimizing Data Mixtures Speeds Up Language Model Pretraining »
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2023 : Retrieval-Augmented Multimodal Language Modeling »
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2023 : Lexinvariant Language Models »
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2023 : PRODIGY: Enabling In-context Learning Over Graphs »
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2023 : Sophia: A Scalable Stochastic Second-order Optimizer for Language Model Pre-training »
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2023 Workshop: ES-FoMo: Efficient Systems for Foundation Models »
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2023 Poster: Whose Opinions Do Language Models Reflect? »
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2023 Poster: RLSbench: Domain Adaptation Under Relaxed Label Shift »
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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? »
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2023 Oral: Evaluating Self-Supervised Learning via Risk Decomposition »
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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 »
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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 »
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2023 Poster: Retrieval-Augmented Multimodal Language Modeling »
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2022 : Distribution Shifts in Healthcare—A Key Barrier to Safe Deployment of Machine Learning Algorithms in the Clinic »
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2022 Workshop: The First Workshop on Pre-training: Perspectives, Pitfalls, and Paths Forward »
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2022 Poster: Rich Feature Construction for the Optimization-Generalization Dilemma »
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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 »
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2022 Oral: Connect, Not Collapse: Explaining Contrastive Learning for Unsupervised Domain Adaptation »
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2022 Poster: Partial and Asymmetric Contrastive Learning for Out-of-Distribution Detection in Long-Tailed Recognition »
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2022 Oral: Partial and Asymmetric Contrastive Learning for Out-of-Distribution Detection in Long-Tailed Recognition »
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2021 Poster: WILDS: A Benchmark of in-the-Wild Distribution Shifts »
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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 »
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2021 Poster: Break-It-Fix-It: Unsupervised Learning for Program Repair »
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2021 Oral: Break-It-Fix-It: Unsupervised Learning for Program Repair »
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2021 Spotlight: Accuracy on the Line: on the Strong Correlation Between Out-of-Distribution and In-Distribution Generalization »
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2021 Poster: Decoupling Exploration and Exploitation for Meta-Reinforcement Learning without Sacrifices »
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2021 Spotlight: Decoupling Exploration and Exploitation for Meta-Reinforcement Learning without Sacrifices »
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2021 Poster: Catformer: Designing Stable Transformers via Sensitivity Analysis »
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2020 : "AutoGluon and Distillation" by Alex Smola »
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2020 : Keynote #3 Percy Liang »
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2020 Poster: Concept Bottleneck Models »
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2020 Poster: Graph-based, Self-Supervised Program Repair from Diagnostic Feedback »
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2020 Poster: Understanding Self-Training for Gradual Domain Adaptation »
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2020 Poster: Understanding and Mitigating the Tradeoff between Robustness and Accuracy »
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2020 Poster: An Investigation of Why Overparameterization Exacerbates Spurious Correlations »
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2020 Poster: Robustness to Spurious Correlations via Human Annotations »
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2020 Poster: Feature Noise Induces Loss Discrepancy Across Groups »
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2019 Poster: Deep Factors for Forecasting »
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2019 Oral: Deep Factors for Forecasting »
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2019 Tutorial: A Tutorial on Attention in Deep Learning »
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2018 Poster: Learning Steady-States of Iterative Algorithms over Graphs »
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2018 Poster: Fairness Without Demographics in Repeated Loss Minimization »
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2018 Oral: Fairness Without Demographics in Repeated Loss Minimization »
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2018 Oral: Learning Steady-States of Iterative Algorithms over Graphs »
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2017 Talk: World of Bits: An Open-Domain Platform for Web-Based Agents »
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2017 Talk: Canopy --- Fast Sampling with Cover Trees »
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2017 Poster: Developing Bug-Free Machine Learning Systems With Formal Mathematics »
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2017 Talk: Developing Bug-Free Machine Learning Systems With Formal Mathematics »
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2017 Poster: Convexified Convolutional Neural Networks »
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2017 Poster: Understanding Black-box Predictions via Influence Functions »
Pang Wei Koh · Percy Liang -
2017 Poster: Wasserstein Generative Adversarial Networks »
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2017 Talk: Wasserstein Generative Adversarial Networks »
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2017 Talk: Understanding Black-box Predictions via Influence Functions »
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