Neural Information Processing Systems Foundation, Inc. (NeurIPS)

  • Certified Minimax Unlearning with Generalization Rates and Deletion Capacity

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Certified Minimax Unlearning with Generalization Rates and Deletion Capacity

    Jiaqi Liu, Jian Lou, Zhan Qin, Kui Ren p62821-62852 from Advances in Neural Information Processing Systems 36
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  • Certified Robustness for Deep Equilibrium Models via Serialized Random Smoothing

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Certified Robustness for Deep Equilibrium Models via Serialized Random Smoothing

    Weizhi Gao, Zhichao Hou, Xiaorui Liu, Han Xu p1370-1401 from Advances in Neural Information Processing Systems 37
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  • Certified Robustness via Dynamic Margin Maximization and Improved Lipschitz Regularization

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Certified Robustness via Dynamic Margin Maximization and Improved Lipschitz Regularization

    Rama Chellappa, Taha Entesari, Mahyar Fazlyab, Aniket Roy p34451-34464 from Advances in Neural Information Processing Systems 36
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  • Certifying Robust Graph Classification Under Orthogonal Gromov-Wasserstein Threats

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Certifying Robust Graph Classification Under Orthogonal Gromov-Wasserstein Threats

    Hongwei Jin, Zishun Yu, Xinhua Zhang p1737-1750 from Advances in Neural Information Processing Systems 35
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  • Certifying Some Distributional Fairness with Subpopulation Decomposition

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Certifying Some Distributional Fairness with Subpopulation Decomposition

    Mintong Kang, Bo Li, Linyi Li, Yang Liu, Maurice Weber, Ce Zhang p31045-31058 from Advances in Neural Information Processing Systems 35
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  • CGLB: Benchmark Tasks for Continual Graph Learning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    CGLB: Benchmark Tasks for Continual Graph Learning

    Dongjin Song, Dacheng Tao, Xikun Zhang p13006-13021 from Advances in Neural Information Processing Systems 35
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  • Chain of Agents: Large Language Models Collaborating on Long-Context Tasks

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Chain of Agents: Large Language Models Collaborating on Long-Context Tasks

    Sercan Arık, Yanfei Chen, Tomas Pfister, Ruoxi Sun, Rui Zhang, Yusen Zhang p132208-132237 from Advances in Neural Information Processing Systems 37
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  • Chain of Preference Optimization: Improving Chain-of-Thought Reasoning in LLMs

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Chain of Preference Optimization: Improving Chain-of-Thought Reasoning in LLMs

    Chao Du, Wei Gao, Min Lin, Qian Liu, Tianyu Pang, Xuan Zhang p333-356 from Advances in Neural Information Processing Systems 37
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  • Chain of Thought Imitation with Procedure Cloning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Chain of Thought Imitation with Procedure Cloning

    Pieter Abbeel, Ofir Nachum, Dale Schuurmans, Mengjiao Sherry Yang p36366-36381 from Advances in Neural Information Processing Systems 35
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  • Chain of Thoughtlessness? An Analysis of CoT in Planning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Chain of Thoughtlessness? An Analysis of CoT in Planning

    Subbarao Kambhampati, Kaya Stechly, Karthik Valmeekam p29106-29141 from Advances in Neural Information Processing Systems 37
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  • Chain-Of-Thought Prompting Elicits Reasoning in Large Language Models

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Chain-Of-Thought Prompting Elicits Reasoning in Large Language Models

    Maarten Bosma, Ed Chi, Brian Ichter, Quoc V Le, Dale Schuurmans, Xuezhi Wang, Jason Wei, Fei Xia, Denny Zhou p24824-24837 from Advances in Neural Information Processing Systems 35
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  • Chain-of-Thought Reasoning Without Prompting

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Chain-of-Thought Reasoning Without Prompting

    Xuezhi Wang, Denny Zhou p66383-66409 from Advances in Neural Information Processing Systems 37
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  • Challenges of Generating Structurally Diverse Graphs

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Challenges of Generating Structurally Diverse Graphs

    Mikhail Mironov, Liudmila Prokhorenkova, Fedor Velikonivtsev p57993-58022 from Advances in Neural Information Processing Systems 37
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  • Challenging Common Assumptions in Convex Reinforcement Learning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Challenging Common Assumptions in Convex Reinforcement Learning

    Piersilvio De Bartolomeis, Riccardo De Santi, Mirco Mutti, Marcello Restelli p4489-4502 from Advances in Neural Information Processing Systems 35
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  • Chameleon: Plug-and-Play Compositional Reasoning with Large Language Models

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Chameleon: Plug-and-Play Compositional Reasoning with Large Language Models

    Kai-Wei Chang, Hao Cheng, Michel Galley, Jianfeng Gao, Pan Lu, Baolin Peng, Ying Nian Wu, Song-Chun Zhu p43447-43478 from Advances in Neural Information Processing Systems 36
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  • CHAMMI: A benchmark for channel-adaptive models in microscopy imaging

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    CHAMMI: A benchmark for channel-adaptive models in microscopy imaging

    Juan C. Caicedo, Zitong Sam Chen, Michael Doron, Nikita Moshkov, Chau Pham, Bryan Plummer, Siqi Wang p19700-19713 from Advances in Neural Information Processing Systems 36
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  • Chanakya: Learning Runtime Decisions for Adaptive Real-Time Perception

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Chanakya: Learning Runtime Decisions for Adaptive Real-Time Perception

    Vaibhav Balloli, Tanuja Ganu, Anurag Ghosh, Akshay Nambi, Aditya Singh p55668-55680 from Advances in Neural Information Processing Systems 36
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  • Change Event Dataset for Discovery from Spatio-Temporal Remote Sensing Imagery

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Change Event Dataset for Discovery from Spatio-Temporal Remote Sensing Imagery

    Kavita Bala, Bharath Hariharan, Utkarsh Mall p27484-27496 from Advances in Neural Information Processing Systems 35
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  • Change point detection and inference in multivariate non-parametric models under mixing conditions

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Change point detection and inference in multivariate non-parametric models under mixing conditions

    Carlos Misael Madrid Padilla, Oscar Hernan Madrid Padilla, Daren Wang, Haotian Xu, Yi Yu p21081-21134 from Advances in Neural Information Processing Systems 36
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  • Change-Point Detection for Sparse and Dense Functional Data in General Dimensions

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Change-Point Detection for Sparse and Dense Functional Data in General Dimensions

    Carlos Misael Madrid Padilla, Daren Wang, Yi Yu, Zifeng Zhao p37121-37133 from Advances in Neural Information Processing Systems 35
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  • Changing the Training Data Distribution to Reduce Simplicity Bias Improves In-distribution Generalization

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Changing the Training Data Distribution to Reduce Simplicity Bias Improves In-distribution Generalization

    Eric Gan, Paymon Haddad, Baharan Mirzasoleiman, Tuan Nguyen p68854-68896 from Advances in Neural Information Processing Systems 37
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  • ChaosBench: A Multi-Channel, Physics-Based Benchmark for Subseasonal-to-Seasonal Climate Prediction

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    ChaosBench: A Multi-Channel, Physics-Based Benchmark for Subseasonal-to-Seasonal Climate Prediction

    Julius Busecke, Pierre Gentine, Aditya Grover, Juan Nathaniel, Tung Nguyen, Yongquan Qu, Sungduk Yu p43715-43729 from Advances in Neural Information Processing Systems 37
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  • Chaotic Dynamics Are Intrinsic to Neural Network Training with SGD

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Chaotic Dynamics Are Intrinsic to Neural Network Training with SGD

    Maximilian Granz, Luis Herrmann, Tim Landgraf p5219-5229 from Advances in Neural Information Processing Systems 35
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  • Chaotic Regularization and Heavy-Tailed Limits for Deterministic Gradient Descent

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Chaotic Regularization and Heavy-Tailed Limits for Deterministic Gradient Descent

    Soon Hoe Lim, Umut Simsekli, Yijun Wan p26590-26602 from Advances in Neural Information Processing Systems 35
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