Neural Information Processing Systems Foundation, Inc. (NeurIPS)

  • Explaining Predictive Uncertainty with Information Theoretic Shapley Values

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Explaining Predictive Uncertainty with Information Theoretic Shapley Values

    Ido Guy, Richard Mudd, Joshua O'Hara, Niek Tax, David Watson p7330-7350 from Advances in Neural Information Processing Systems 36
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  • Explaining Preferences with Shapley Values

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Explaining Preferences with Shapley Values

    Siu Lun Chau, Jaime Ferrando Huertas, Robert Hu, Dino Sejdinovic p27664-27677 from Advances in Neural Information Processing Systems 35
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  • Explaining the Uncertain: Stochastic Shapley Values for Gaussian Process Models

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Explaining the Uncertain: Stochastic Shapley Values for Gaussian Process Models

    Siu Lun Chau, Krikamol Muandet, Dino Sejdinovic p50769-50795 from Advances in Neural Information Processing Systems 36
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  • Explaining V1 Properties with a Biologically Constrained Deep Learning Architecture

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Explaining V1 Properties with a Biologically Constrained Deep Learning Architecture

    Michael Beyeler, Jacob Granley, Galen Pogoncheff p13908-13930 from Advances in Neural Information Processing Systems 36
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  • Explanations that reveal all through the de?nition of encoding

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Explanations that reveal all through the de?nition of encoding

    Nhi Nguyen, Aahlad Puli, Rajesh Ranganath p99965-100006 from Advances in Neural Information Processing Systems 37
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  • Explicable Policy Search

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Explicable Policy Search

    Ze Gong, Yu Tony Zhang p38859-38872 from Advances in Neural Information Processing Systems 35
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  • Explicit Eigenvalue Regularization Improves Sharpness-Aware Minimization

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Explicit Eigenvalue Regularization Improves Sharpness-Aware Minimization

    Mehrtash Harandi, Trung Le, Haocheng Luo, Tung Pham, Dinh Phung, Tuan Truong p4424-4453 from Advances in Neural Information Processing Systems 37
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  • Explicit Tradeoffs Between Adversarial and Natural Distributional Robustness

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Explicit Tradeoffs Between Adversarial and Natural Distributional Robustness

    Kiarash Banihashem, Soheil Feizi, Mazda Moayeri p38761-38774 from Advances in Neural Information Processing Systems 35
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  • Exploit Reward Shifting in Value-Based Deep-RL: Optimistic Curiosity-Based Exploration and Conservative Exploitation Via Linear Reward Shaping

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Exploit Reward Shifting in Value-Based Deep-RL: Optimistic Curiosity-Based Exploration and Conservative Exploitation Via Linear Reward Shaping

    Jian Guo, Lei Han, Xiaoteng Ma, Hao Sun, Rui Yang, Bolei Zhou p37719-37734 from Advances in Neural Information Processing Systems 35
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  • Exploitability Minimization in Games and Beyond

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Exploitability Minimization in Games and Beyond

    Denizalp Goktas, Amy Greenwald p4857-4873 from Advances in Neural Information Processing Systems 35
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  • Exploitation of a Latent Mechanism in Graph Contrastive Learning: Representation Scattering

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Exploitation of a Latent Mechanism in Graph Contrastive Learning: Representation Scattering

    Dongxiao He, Lianze Shan, Zhen Wang, Hengrui Zhang, Weixiong Zhang, Jitao Zhao p115351-115376 from Advances in Neural Information Processing Systems 37
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  • Exploiting Activation Sparsity with Dense to Dynamic-k Mixture-of-Experts Conversion

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Exploiting Activation Sparsity with Dense to Dynamic-k Mixture-of-Experts Conversion

    Mikołaj Piórczyński, Simone Scardapane, Filip Szatkowski, Bartosz Wójcik p43245-43273 from Advances in Neural Information Processing Systems 37
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  • Exploiting Connections between Lipschitz Structures for Certifiably Robust Deep Equilibrium Models

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Exploiting Connections between Lipschitz Structures for Certifiably Robust Deep Equilibrium Models

    Alexandre Araujo, Siddharth Garg, Aaron Havens, Bin Hu, Farshad Khorrami p21658-21674 from Advances in Neural Information Processing Systems 36
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  • Exploiting Contextual Objects and Relations for 3D Visual Grounding

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Exploiting Contextual Objects and Relations for 3D Visual Grounding

    Weiming Hu, Bing Li, Peng Li, Wei Liu, Zhongang Qi, Ying Shan, Yan Wang, Yan Xu, Li Yang, Weiping Yang, Chunfeng Yuan, Ziqi Zhang p49542-49554 from Advances in Neural Information Processing Systems 36
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  • Exploiting Correlated Auxiliary Feedback in Parameterized Bandits

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Exploiting Correlated Auxiliary Feedback in Parameterized Bandits

    Zhongxiang Dai, Bryan Kian Hsiang Low, Yao Shu, Arun Verma p4430-4451 from Advances in Neural Information Processing Systems 36
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  • Exploiting Descriptive Completeness Prior for Cross Modal Hashing with Incomplete Labels

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Exploiting Descriptive Completeness Prior for Cross Modal Hashing with Incomplete Labels

    Haoyang Luo, Yadan Luo, Zheng Zhang p50826-50849 from Advances in Neural Information Processing Systems 37
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  • Exploiting hidden structures in non-convex games for convergence to Nash equilibrium

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Exploiting hidden structures in non-convex games for convergence to Nash equilibrium

    Panayotis Mertikopoulos, Georgios Piliouras, Iosif Sakos, Emmanouil-Vasileios Vlatakis-Gkaragkounis p66979-67006 from Advances in Neural Information Processing Systems 36
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  • Exploiting LLM Quantization

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Exploiting LLM Quantization

    Kazuki Egashira, Jingxuan He, Robin Staab, Martin Vechev, Mark Vero p41709-41732 from Advances in Neural Information Processing Systems 37
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  • Exploiting Representation Curvature for Boundary Detection in Time Series

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Exploiting Representation Curvature for Boundary Detection in Time Series

    Byung Lee, Jae-Gil Lee, Jaehyun Park, Yooju Shin, Hwanjun Song, Susik Yoon p5974-5995 from Advances in Neural Information Processing Systems 37
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  • Exploiting Semantic Relations for Glass Surface Detection

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Exploiting Semantic Relations for Glass Surface Detection

    Rynson Lau, Jiaying Lin, Yuen-Hei Yeung p22490-22504 from Advances in Neural Information Processing Systems 35
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  • Exploiting the Relationship Between Kendall's Rank Correlation and Cosine Similarity for Attribution Protection

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Exploiting the Relationship Between Kendall's Rank Correlation and Cosine Similarity for Attribution Protection

    Adams Wai Kin Kong, Fan Wang p20580-20591 from Advances in Neural Information Processing Systems 35
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  • Exploiting the Replay Memory Before Exploring the Environment: Enhancing Reinforcement Learning Through Empirical MDP Iteration

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Exploiting the Replay Memory Before Exploring the Environment: Enhancing Reinforcement Learning Through Empirical MDP Iteration

    Chao Gao, Martin Müller, Han Wang, Chenjun Xiao, Bo Xu, Hongming Zhang p85658-85692 from Advances in Neural Information Processing Systems 37
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  • Exploration by Learning Diverse Skills through Successor State Representations

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Exploration by Learning Diverse Skills through Successor State Representations

    Yann Besse, Paul-Antoine Le Tolguenec, Emmanuel Rachelson, Florent Teichteil-Konigsbuch, Dennis Wilson p75277-75301 from Advances in Neural Information Processing Systems 37
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  • Exploration Via Elliptical Episodic Bonuses

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Exploration Via Elliptical Episodic Bonuses

    Mikael Henaff, Minqi Jiang, Roberta Raileanu, Tim Rocktäschel p37631-37646 from Advances in Neural Information Processing Systems 35
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