Neural Information Processing Systems Foundation, Inc. (NeurIPS)

  • A Fair Federated Learning Method for Handling Client Participation Probability Inconsistencies in Heterogeneous Environments

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    A Fair Federated Learning Method for Handling Client Participation Probability Inconsistencies in Heterogeneous Environments

    Siyuan Wu, Yongzhe Jia, Haolong Xiang, Xiaolong Xu, Xuyun Zhang, Lianyong Qi, Wanchun Dou p166678-166707 from Advances in Neural Information Processing Systems 38
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  • A Fast and Accurate Estimator for Large Scale Linear Model via Data Averaging

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    A Fast and Accurate Estimator for Large Scale Linear Model via Data Averaging

    Rui Wang, Yanyan Ouyang, Yu Panpan, Wangli Xu p34917-34927 from Advances in Neural Information Processing Systems 36
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  • A Fast Convoluted Story: Scaling Probabilistic Inference for Integer Arithmetics

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    A Fast Convoluted Story: Scaling Probabilistic Inference for Integer Arithmetics

    Lennert De Smet, Pedro Zuidberg Dos Martires p102456-102478 from Advances in Neural Information Processing Systems 37
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  • A fast heuristic to optimize time-space tradeoff for large models

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    A fast heuristic to optimize time-space tradeoff for large models

    Akifumi Imanishi, Zijian Xu, Masayuki Takagi, Sixue Wang, Emilio Castillo p49679-49702 from Advances in Neural Information Processing Systems 36
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  • A Fast Post-Training Pruning Framework for Transformers

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    A Fast Post-Training Pruning Framework for Transformers

    Woosuk Kwon, Sehoon Kim, Michael Mahoney, Joseph Hassoun, Kurt Keutzer, Amir Gholami p24101-24116 from Advances in Neural Information Processing Systems 35
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  • A Fast Scale-Invariant Algorithm for Non-Negative Least Squares with Non-Negative Data

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    A Fast Scale-Invariant Algorithm for Non-Negative Least Squares with Non-Negative Data

    Jelena Diakonikolas, Chenghui Li, Swati Padmanabhan, Chaobing Song p6264-6277 from Advances in Neural Information Processing Systems 35
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  • A faster training algorithm for regression trees with linear leaves, and an analysis of its complexity

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    A faster training algorithm for regression trees with linear leaves, and an analysis of its complexity

    Kuat Gazizov, Miguel A. Carreira-Perpinan p147022-147043 from Advances in Neural Information Processing Systems 38
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  • A Few Expert Queries Suffices for Sample-Efficient RL with Resets and Linear Value Approximation

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    A Few Expert Queries Suffices for Sample-Efficient RL with Resets and Linear Value Approximation

    Philip Amortila, Nan Jiang, Dhruv Madeka, Dean Foster p29637-29648 from Advances in Neural Information Processing Systems 35
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  • A Few Moments Please: Scalable Graphon Learning via Moment Matching

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    A Few Moments Please: Scalable Graphon Learning via Moment Matching

    Reza Ramezanpour, Victor Manuel Tenorio Gomez, Antonio G. Marques, Ashutosh Sabharwal, Santiago Segarra p1673-1708 from Advances in Neural Information Processing Systems 38
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  • A Finite Sample Analysis of Distributional TD Learning with Linear Function Approximation

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    A Finite Sample Analysis of Distributional TD Learning with Linear Function Approximation

    Yang Peng, Kaicheng Jin, Liangyu Zhang, Zhihua Zhang p189165-189213 from Advances in Neural Information Processing Systems 38
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  • A Finite-Particle Convergence Rate for Stein Variational Gradient Descent

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    A Finite-Particle Convergence Rate for Stein Variational Gradient Descent

    Jiaxin Shi, Lester Mackey p26831-26844 from Advances in Neural Information Processing Systems 36
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  • A Finite-Sample Analysis of Payoff-Based Independent Learning in Zero-Sum Stochastic Games

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    A Finite-Sample Analysis of Payoff-Based Independent Learning in Zero-Sum Stochastic Games

    Zaiwei Chen, Kaiqing Zhang, Eric Mazumdar, Asuman Ozdaglar, Adam Wierman p75826-75883 from Advances in Neural Information Processing Systems 36
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  • A Flexible, Equivariant Framework for Subgraph GNNs via Graph Products and Graph Coarsening

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    A Flexible, Equivariant Framework for Subgraph GNNs via Graph Products and Graph Coarsening

    Guy Bar-Shalom, Yam Eitan, Fabrizio Frasca, Haggai Maron p101168-101222 from Advances in Neural Information Processing Systems 37
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  • A Foundation Model for Zero-shot Logical Query Reasoning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    A Foundation Model for Zero-shot Logical Query Reasoning

    Mikhail Galkin, Jincheng Zhou, Bruno Ribeiro, Jian Tang, Zhaocheng Zhu p54137-54160 from Advances in Neural Information Processing Systems 37
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  • A Fourier Approach to Mixture Learning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    A Fourier Approach to Mixture Learning

    Mingda Qiao, Guru Guruganesh, Ankit Rawat, Kumar Avinava Dubey, Manzil Zaheer p20850-20861 from Advances in Neural Information Processing Systems 35
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  • A Fractional Graph Laplacian Approach to Oversmoothing

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    A Fractional Graph Laplacian Approach to Oversmoothing

    Sohir Maskey, Raffaele Paolino, Aras Bacho, Gitta Kutyniok p13022-13063 from Advances in Neural Information Processing Systems 36
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  • A Framework for Bilevel Optimization on Riemannian Manifolds

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    A Framework for Bilevel Optimization on Riemannian Manifolds

    Andi Han, Bamdev Mishra, Pratik Jawanpuria, Akiko Takeda p103829-103872 from Advances in Neural Information Processing Systems 37
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  • A Framework for Bilevel Optimization that Enables Stochastic and Global Variance Reduction Algorithms

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    A Framework for Bilevel Optimization that Enables Stochastic and Global Variance Reduction Algorithms

    Mathieu Dagréou, Pierre Ablin, Samuel Vaiter, Thomas Moreau p26698-26710 from Advances in Neural Information Processing Systems 35
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  • A Framework for Fast and Stable Representations of Multiparameter Persistent Homology Decompositions

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    A Framework for Fast and Stable Representations of Multiparameter Persistent Homology Decompositions

    David Loiseaux, Mathieu Carrière, Andrew Blumberg p35774-35798 from Advances in Neural Information Processing Systems 36
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  • A Frustratingly Simple Yet Highly Effective Attack Baseline: Over 90% Success Rate Against the Strong Black-box Models of GPT-4.5/4o/o1

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    A Frustratingly Simple Yet Highly Effective Attack Baseline: Over 90% Success Rate Against the Strong Black-box Models of GPT-4.5/4o/o1

    Zhaoyi Li, Xiaohan Zhao, Dong-Dong Wu, Jiacheng Cui, Zhiqiang Shen p50286-50319 from Advances in Neural Information Processing Systems 38
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  • A Full-duplex Speech Dialogue Scheme Based On Large Language Model

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    A Full-duplex Speech Dialogue Scheme Based On Large Language Model

    Peng Wang, Songshuo Lu, Yaohua Tang, Sijie Yan, Wei Xia, Yuanjun Xiong p13372-13403 from Advances in Neural Information Processing Systems 37
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  • A Functional Extension of Semi-Structured Networks

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    A Functional Extension of Semi-Structured Networks

    David Rügamer, Bernard Liew, Zainab Altai, Almond Stöcker p129888-129913 from Advances in Neural Information Processing Systems 37
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  • A General Approximation Lower Bound in Lp Norm, with Applications to Feed-Forward Neural Networks

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    A General Approximation Lower Bound in Lp Norm, with Applications to Feed-Forward Neural Networks

    El Mehdi Achour, Armand Foucault, Sébastien Gerchinovitz, François Malgouyres p22396-22408 from Advances in Neural Information Processing Systems 35
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  • A General Framework for Auditing Differentially Private Machine Learning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    A General Framework for Auditing Differentially Private Machine Learning

    Fred Lu, Joseph Munoz, Maya Fuchs, Tyler Leblond, Elliott Zaresky-Williams, Edward Raff, Francis Ferraro, Brian Testa p4165-4176 from Advances in Neural Information Processing Systems 35
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