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159 Results
Poster
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Tue 14:00 |
PAC-Bayes Compression Bounds So Tight That They Can Explain Generalization Sanae Lotfi · Marc Finzi · Sanyam Kapoor · Andres Potapczynski · Micah Goldblum · Andrew Wilson |
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Workshop
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Machine Learning Explainability from an Information-theoretic Perspective Debargha Ganguly · Debayan Gupta |
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Poster
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Debugging and Explaining Metric Learning Approaches: An Influence Function Based Perspective Ruofan Liu · Yun Lin · XIANGLIN YANG · Jin Song Dong |
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Poster
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Wed 14:00 |
Self-Supervised Fair Representation Learning without Demographics Junyi Chai · Xiaoqian Wang |
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Poster
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Self-Supervised Learning via Maximum Entropy Coding Xin Liu · Zhongdao Wang · Ya-Li Li · Shengjin Wang |
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Poster
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Thu 14:00 |
Self-Supervised Learning with an Information Maximization Criterion Serdar Ozsoy · Shadi Hamdan · Sercan Arik · Deniz Yuret · Alper Erdogan |
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Poster
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Wed 14:00 |
Scalable Interpretability via Polynomials Abhimanyu Dubey · Filip Radenovic · Dhruv Mahajan |
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Poster
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Wed 9:00 |
Neural Basis Models for Interpretability Filip Radenovic · Abhimanyu Dubey · Dhruv Mahajan |
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Poster
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Wed 14:00 |
ProtoX: Explaining a Reinforcement Learning Agent via Prototyping Ronilo Ragodos · Tong Wang · Qihang Lin · Xun Zhou |
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Poster
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Tue 9:00 |
Learn to Explain: Multimodal Reasoning via Thought Chains for Science Question Answering Pan Lu · Swaroop Mishra · Tanglin Xia · Liang Qiu · Kai-Wei Chang · Song-Chun Zhu · Oyvind Tafjord · Peter Clark · Ashwin Kalyan |
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Workshop
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Visual Reinforcement Learning with Self-Supervised 3D Representations Yanjie Ze · Nicklas Hansen · Yinbo Chen · Mohit Jain · Xiaolong Wang |
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Workshop
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Fri 7:10 |
Learning to Look by Self-Prediction Matthew Grimes |