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Workshop
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Fri 17:25
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Ce Zhang: Optimizing Communications and Data for Distributed and Decentralized Learning
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Workshop
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Proximal Compositional Optimization for Distributionally Robust Learning
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Poster
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Thu 13:30
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On Distribution Dependent Sub-Logarithmic Query Time of Learned Indexing
Sepanta Zeighami · Cyrus Shahabi
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Poster
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Thu 13:30
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Learning useful representations for shifting tasks and distributions
Jianyu Zhang · Leon Bottou
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Workshop
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Complementary Benefits of Contrastive Learning and Self-Training Under Distribution Shift
Saurabh Garg · Amrith Setlur · Zachary Lipton · Sivaraman Balakrishnan · Virginia Smith · Aditi Raghunathan
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Poster
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Thu 13:30
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DIFF2: Differential Private Optimization via Gradient Differences for Nonconvex Distributed Learning
Tomoya Murata · Taiji Suzuki
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Poster
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Thu 13:30
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Out-of-Distribution Generalization of Federated Learning via Implicit Invariant Relationships
Yaming Guo · Kai Guo · Xiaofeng Cao · Tieru Wu · Yi Chang
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Workshop
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Towards Understanding Feature Learning in Out-of-Distribution Generalization
Yongqiang Chen · Wei Huang · Kaiwen Zhou · Yatao Bian · Bo Han · James Cheng
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Poster
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Tue 14:00
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Learning Distributions over Quantum Measurement Outcomes
Weiyuan Gong · Scott Aaronson
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Workshop
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Robust Deep Learning via Layerwise Tilted Exponentials
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Poster
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Thu 16:30
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Learning Functional Distributions with Private Labels
Changlong Wu · Yifan Wang · Ananth Grama · Wojciech Szpankowski
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Poster
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Thu 13:30
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Statistical Learning under Heterogenous Distribution Shift
Max Simchowitz · Anurag Ajay · Pulkit Agrawal · Akshay Krishnamurthy
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