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Poster
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Mon 2:30
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MetaShift: A Dataset of Datasets for Evaluating Contextual Distribution Shifts and Training Conflicts
Victor Weixin Liang · James Y Zou
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Poster
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Tue 18:30
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A Unified Wasserstein Distributional Robustness Framework for Adversarial Training
Anh Bui · Trung Le · Quan Tran · He Zhao · Dinh Phung
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Poster
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Tue 2:30
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Permutation Compressors for Provably Faster Distributed Nonconvex Optimization
Rafał Szlendak · Alexander Tyurin · Peter Richtarik
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Poster
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Tue 18:30
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Training Transition Policies via Distribution Matching for Complex Tasks
Ju-Seung Byun · Andrew Perrault
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Poster
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Thu 18:30
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Parallel Training of GRU Networks with a Multi-Grid Solver for Long Sequences
Gordon Euhyun Moon · Eric Cyr
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Poster
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Mon 10:30
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Group-based Interleaved Pipeline Parallelism for Large-scale DNN Training
PengCheng Yang · Xiaoming Zhang · Wenpeng Zhang · Ming Yang · Hong Wei
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Poster
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Wed 18:30
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PipeGCN: Efficient Full-Graph Training of Graph Convolutional Networks with Pipelined Feature Communication
Cheng Wan · Youjie Li · Cameron Wolfe · Anastasios Kyrillidis · Nam Sung Kim · Yingyan Lin
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Poster
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Mon 10:30
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Learn Locally, Correct Globally: A Distributed Algorithm for Training Graph Neural Networks
Morteza Ramezani · Weilin Cong · Mehrdad Mahdavi · Mahmut Kandemir · Anand Sivasubramaniam
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