Neural Information Processing Systems Foundation, Inc. (NeurIPS)

  • Provable Tempered Overfitting of Minimal Nets and Typical Nets

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Provable Tempered Overfitting of Minimal Nets and Typical Nets

    Itay Evron, Itamar Harel, William Hoza, Daniel Soudry, Nathan Srebro, Gal Vardi p53458-53524 from Advances in Neural Information Processing Systems 37
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  • Provable Training for Graph Contrastive Learning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Provable Training for Graph Contrastive Learning

    Nian Liu, Chuan Shi, Xiao Wang, Yue Yu, Mengmei Zhang p50327-50345 from Advances in Neural Information Processing Systems 36
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  • Provably (More) Sample-Efficient Offline RL with Options

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Provably (More) Sample-Efficient Offline RL with Options

    Xiaoyan Hu, Ho-Fung Leung p68784-68797 from Advances in Neural Information Processing Systems 36
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  • Provably Adversarially Robust Detection of Out-Of-Distribution Data (Almost) for Free

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Provably Adversarially Robust Detection of Out-Of-Distribution Data (Almost) for Free

    Julian Bitterwolf, Matthias Hein, Alexander Meinke p30167-30180 from Advances in Neural Information Processing Systems 35
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  • Provably and Practically Efficient Adversarial Imitation Learning with General Function Approximation

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Provably and Practically Efficient Adversarial Imitation Learning with General Function Approximation

    Ruishuo Chen, Yihao Sun, Tian Xu, Yang Yu, Zhilong Zhang p66108-66146 from Advances in Neural Information Processing Systems 37
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  • Provably Bounding Neural Network Preimages

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Provably Bounding Neural Network Preimages

    Christopher Brix, Krishnamurthy Dvijotham, J. Zico Kolter, Suhas Kotha, Huan Zhang p80270-80290 from Advances in Neural Information Processing Systems 36
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  • Provably Efficient Algorithm for Nonstationary Low-Rank MDPs

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Provably Efficient Algorithm for Nonstationary Low-Rank MDPs

    Yuan Cheng, Yingbin Liang, Jing Yang p6330-6372 from Advances in Neural Information Processing Systems 36
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  • Provably Efficient Interactive-Grounded Learning with Personalized Reward

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Provably Efficient Interactive-Grounded Learning with Personalized Reward

    Haipeng Luo, Paul Mineiro, Mengxiao Zhang, Yuheng Zhang p121073-121098 from Advances in Neural Information Processing Systems 37
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  • Provably Efficient Model-Free Constrained RL with Linear Function Approximation

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Provably Efficient Model-Free Constrained RL with Linear Function Approximation

    Arnob Ghosh, Ness Shroff, Xingyu Zhou p13303-13315 from Advances in Neural Information Processing Systems 35
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  • Provably Efficient Offline Goal-Conditioned Reinforcement Learning with General Function Approximation and Single-Policy Concentrability

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Provably Efficient Offline Goal-Conditioned Reinforcement Learning with General Function Approximation and Single-Policy Concentrability

    Amy Zhang, Hanlin Zhu p4177-4198 from Advances in Neural Information Processing Systems 36
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  • Provably Efficient Offline Multi-Agent Reinforcement Learning Via Strategy-Wise Bonus

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Provably Efficient Offline Multi-Agent Reinforcement Learning Via Strategy-Wise Bonus

    Qiwen Cui, Simon Du p11739-11751 from Advances in Neural Information Processing Systems 35
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  • Provably Efficient Offline Reinforcement Learning in Regular Decision Processes

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Provably Efficient Offline Reinforcement Learning in Regular Decision Processes

    Roberto Cipollone, Anders Jonsson, Alessandro Ronca, Mohammad Sadegh Talebi p39395-39428 from Advances in Neural Information Processing Systems 36
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  • Provably Efficient Reinforcement Learning in Partially Observable Dynamical Systems

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Provably Efficient Reinforcement Learning in Partially Observable Dynamical Systems

    Nathan Kallus, Jason Lee, Ayush Sekhari, Wen Sun, Masatoshi Uehara p578-592 from Advances in Neural Information Processing Systems 35
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  • Provably Efficient Reinforcement Learning with Multinomial Logit Function Approximation

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Provably Efficient Reinforcement Learning with Multinomial Logit Function Approximation

    Long-Fei Li, Yu-Jie Zhang, Peng Zhao, Zhi-Hua Zhou p58539-58573 from Advances in Neural Information Processing Systems 37
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  • Provably Expressive Temporal Graph Networks

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Provably Expressive Temporal Graph Networks

    Vikas Garg, Samuel Kaski, Diego Mesquita, Amauri Souza p32257-32269 from Advances in Neural Information Processing Systems 35
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  • Provably Fast Convergence of Independent Natural Policy Gradient for Markov Potential Games

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Provably Fast Convergence of Independent Natural Policy Gradient for Markov Potential Games

    P. R. Kumar, Tao Liu, Shahin Shahrampour, Youbang Sun, Ruida Zhou p43951-43971 from Advances in Neural Information Processing Systems 36
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  • Provably Fast Finite Particle Variants of SVGD via Virtual Particle Stochastic Approximation

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Provably Fast Finite Particle Variants of SVGD via Virtual Particle Stochastic Approximation

    Aniket Das, Dheeraj Nagaraj p49748-49760 from Advances in Neural Information Processing Systems 36
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  • Provably Faster Algorithms for Bilevel Optimization via Without-Replacement Sampling

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Provably Faster Algorithms for Bilevel Optimization via Without-Replacement Sampling

    Heng Huang, Junyi Li p70520-70556 from Advances in Neural Information Processing Systems 37
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  • Provably Feedback-Efficient Reinforcement Learning Via Active Reward Learning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Provably Feedback-Efficient Reinforcement Learning Via Active Reward Learning

    Dingwen Kong, Lin Yang p11063-11078 from Advances in Neural Information Processing Systems 35
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  • Provably Mitigating Overoptimization in RLHF: Your SFT Loss is Implicitly an Adversarial Regularizer

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Provably Mitigating Overoptimization in RLHF: Your SFT Loss is Implicitly an Adversarial Regularizer

    Jose Blanchet, Hongyi Guo, Boyi Liu, Zhihan Liu, Miao Lu, Zhaoran Wang, Yingxiang Yang, Shenao Zhang p138663-138697 from Advances in Neural Information Processing Systems 37
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  • Provably Optimal Memory Capacity for Modern Hopfield Models: Transformer-Compatible Dense Associative Memories as Spherical Codes

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Provably Optimal Memory Capacity for Modern Hopfield Models: Transformer-Compatible Dense Associative Memories as Spherical Codes

    Jerry Yao-Chieh Hu, Han Liu, Dennis Wu p70693-70729 from Advances in Neural Information Processing Systems 37
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  • Provably Robust Score-Based Diffusion Posterior Sampling for Plug-and-Play Image Reconstruction

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Provably Robust Score-Based Diffusion Posterior Sampling for Plug-and-Play Image Reconstruction

    Yuejie Chi, Xingyu Xu p36148-36184 from Advances in Neural Information Processing Systems 37
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  • Provably Robust Temporal Difference Learning for Heavy-Tailed Rewards

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Provably Robust Temporal Difference Learning for Heavy-Tailed Rewards

    Semih Cayci, Atilla Eryilmaz p25693-25711 from Advances in Neural Information Processing Systems 36
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  • Provably Safe Neural Network Controllers via Differential Dynamic Logic

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Provably Safe Neural Network Controllers via Differential Dynamic Logic

    Stefan Mitsch, André Platzer, Samuel Teuber p1586-1624 from Advances in Neural Information Processing Systems 37
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