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Poster
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Wed 8:45
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H-nobs: Achieving Certified Fairness and Robustness in Distributed Learning on Heterogeneous Datasets
Guanqiang Zhou · Ping Xu · Ping Xu · Yue Wang · Zhi Tian
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Workshop
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Sat 14:50
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Closing Remarks
Jean Kossaifi
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Poster
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Wed 8:45
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Reward Scale Robustness for Proximal Policy Optimization via DreamerV3 Tricks
Ryan Sullivan · Akarsh Kumar · Shengyi Huang · John Dickerson · Joseph Suarez
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Poster
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Thu 8:45
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2Direction: Theoretically Faster Distributed Training with Bidirectional Communication Compression
Alexander Tyurin · Peter Richtarik
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Poster
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Wed 15:00
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Adaptive SGD with Polyak stepsize and Line-search: Robust Convergence and Variance Reduction
Xiaowen Jiang · Sebastian Stich
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Workshop
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Invariance & Causal Representation Learning: Prospects and Limitations
Simon Bing · Jonas Wahl · Urmi Ninad · Jakob Runge
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Poster
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Tue 15:15
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Adjustable Robust Reinforcement Learning for Online 3D Bin Packing
Yuxin Pan · Yize Chen · Fangzhen Lin
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Poster
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Wed 8:45
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Delayed Algorithms for Distributed Stochastic Weakly Convex Optimization
Wenzhi Gao · Qi Deng
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Poster
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Tue 15:15
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Characterizing the Optimal 0−1 Loss for Multi-class Classification with a Test-time Attacker
Sihui Dai · Wenxin Ding · Arjun Nitin Bhagoji · Daniel Cullina · Heather Zheng · Ben Zhao · Prateek Mittal
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Workshop
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Large-scale Non-convex Stochastic Constrained Distributionally Robust Optimization
Qi Zhang · Shaofeng Zou · Yi Zhou · Lixin Shen · Ashley Prater-Bennette
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Poster
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Wed 8:45
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DropCompute: simple and more robust distributed synchronous training via compute variance reduction
Niv Giladi · Shahar Gottlieb · moran shkolnik · Asaf Karnieli · Ron Banner · Elad Hoffer · Kfir Y. Levy · Daniel Soudry
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Poster
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Wed 8:45
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GradOrth: A Simple yet Efficient Out-of-Distribution Detection with Orthogonal Projection of Gradients
Sima Behpour · Thang Long Doan · Xin Li · Wenbin He · Liang Gou · Liu Ren
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