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32 Results
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Poster
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Thu 16:30 |
Improving Generalization in Federated Learning with Model-Data Mutual Information Regularization: A Posterior Inference Approach Hao Zhang · Chenglin Li · Nuowen Kan · Ziyang Zheng · Wenrui Dai · Junni Zou · Hongkai Xiong |
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Poster
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Thu 11:00 |
Exponential Quantum Communication Advantage in Distributed Inference and Learning Dar Gilboa · Hagay Michaeli · Daniel Soudry · Jarrod McClean |
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Poster
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Thu 11:00 |
Neural Collapse Inspired Feature Alignment for Out-of-Distribution Generalization Zhikang Chen · Min Zhang · Sen Cui · Haoxuan Li · Gang Niu · Mingming Gong · Changshui Zhang · Kun Zhang |
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Workshop
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Compositional Risk Minimization Divyat Mahajan · Mohammad Pezeshki · Ioannis Mitliagkas · Kartik Ahuja · Pascal Vincent |
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Poster
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Fri 16:30 |
Optimizing over Multiple Distributions under Generalized Quasar-Convexity Condition Ding Shihong · Long Yang · Luo Luo · Cong Fang |
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Workshop
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Can Bayesian Neural Networks Make Confident Predictions? Katharine Fisher |
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Workshop
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Multi-Output Distributional Fairness via Post-Processing Gang Li · Qihang Lin · Ayush Ghosh · Tianbao Yang |
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Poster
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Thu 16:30 |
Generalize or Detect? Towards Robust Semantic Segmentation Under Multiple Distribution Shifts Zhitong Gao · Bingnan Li · Mathieu Salzmann · Xuming He |
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Workshop
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Sat 17:27 |
Multi-Output Distributional Fairness via Post-Processing Gang Li · Qihang Lin · Ayush Ghosh · Tianbao Yang |
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Poster
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Wed 16:30 |
FOOGD: Federated Collaboration for Both Out-of-distribution Generalization and Detection Xinting Liao · Weiming Liu · Pengyang Zhou · Fengyuan Yu · Jiahe Xu · Jun Wang · Wenjie Wang · Chaochao Chen · Xiaolin Zheng |
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Workshop
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Task-Relevant Covariance from Manifold Capacity Theory Improves Robustness in Deep Networks William Yang · Chi-Ning Chou · SueYeon Chung |
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Poster
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Wed 11:00 |
Compositional Generalization Across Distributional Shifts with Sparse Tree Operations Paul Soulos · Henry Conklin · Mattia Opper · Paul Smolensky · Jianfeng Gao · Roland Fernandez |