Paper

  • On the Learning Mechanisms in Physical Reasoning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    On the Learning Mechanisms in Physical Reasoning

    Shiqian Li, Kewen Wu, Chi Zhang, Yixin Zhu p28252-28265 from Advances in Neural Information Processing Systems 35
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  • On the Limitations of Fractal Dimension as a Measure of Generalization

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    On the Limitations of Fractal Dimension as a Measure of Generalization

    Charlie Tan, Inés García-Redondo, Qiquan Wang, Michael Bronstein, Anthea Monod p60309-60334 from Advances in Neural Information Processing Systems 37
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  • On the Limitations of Stochastic Pre-Processing Defenses

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    On the Limitations of Stochastic Pre-Processing Defenses

    Yue Gao, I Shumailov, Kassem Fawaz, Nicolas Papernot p24280-24294 from Advances in Neural Information Processing Systems 35
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  • On the Minimax Regret for Contextual Linear Bandits and Multi-Armed Bandits with Expert Advice

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    On the Minimax Regret for Contextual Linear Bandits and Multi-Armed Bandits with Expert Advice

    Shinji Ito p61793-61812 from Advances in Neural Information Processing Systems 37
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  • On the Minimax Regret for Online Learning with Feedback Graphs

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    On the Minimax Regret for Online Learning with Feedback Graphs

    Khaled Eldowa, Emmanuel Esposito, Tom Cesari, Nicolò Cesa-Bianchi p46122-46133 from Advances in Neural Information Processing Systems 36
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  • On the Necessity of Collaboration for Online Model Selection with Decentralized Data

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    On the Necessity of Collaboration for Online Model Selection with Decentralized Data

    Junfan Li, Zheshun Wu, Zenglin Xu, Irwin King p85583-85629 from Advances in Neural Information Processing Systems 37
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  • On the Need for a Language Describing Distribution Shifts: Illustrations on Tabular Datasets

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    On the Need for a Language Describing Distribution Shifts: Illustrations on Tabular Datasets

    Jiashuo Liu, Tianyu Wang, Peng Cui, Hongseok Namkoong p51371-51408 from Advances in Neural Information Processing Systems 36
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  • On the Noise Robustness of In-Context Learning for Text Generation

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    On the Noise Robustness of In-Context Learning for Text Generation

    Hongfu Gao, Feipeng Zhang, Wenyu Jiang, Jun Shu, Feng Zheng, Hongxin Wei p16569-16600 from Advances in Neural Information Processing Systems 37
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  • On the Non-Universality of Deep Learning: Quantifying the Cost of Symmetry

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    On the Non-Universality of Deep Learning: Quantifying the Cost of Symmetry

    Emmanuel Abbe, Enric Boix-Adsera p17188-17201 from Advances in Neural Information Processing Systems 35
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  • ON THE OPERATIONAL BEHAVIOR OF PACKED-BED THERMAL ENERGY STORAGE: A SECOND-LAW OF THERMODYNAMICS APPROACH TO DETERMINE THE INSTANTANEOUS ENERGY CONTENT

    ECOS 2024

    ON THE OPERATIONAL BEHAVIOR OF PACKED-BED THERMAL ENERGY STORAGE: A SECOND-LAW OF THERMODYNAMICS APPROACH TO DETERMINE THE INSTANTANEOUS ENERGY CONTENT

    Ignacio Calderón-Vásquez, José M. Cardemil, F. G. Battisti p13-23 from 37th International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems (ECOS 2024)
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  • On the Optimal Time Complexities in Decentralized Stochastic Asynchronous Optimization

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    On the Optimal Time Complexities in Decentralized Stochastic Asynchronous Optimization

    Alexander Tyurin, Peter Richtárik p122652-122705 from Advances in Neural Information Processing Systems 37
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  • On the Optimality of Dilated Entropy and Lower Bounds for Online Learning in Extensive-Form Games

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    On the Optimality of Dilated Entropy and Lower Bounds for Online Learning in Extensive-Form Games

    Zhiyuan Fan, Christian Kroer, Gabriele Farina p88373-88409 from Advances in Neural Information Processing Systems 37
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