Paper

  • Sampling from Log-Concave Distributions with Infinity-Distance Guarantees

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Sampling from Log-Concave Distributions with Infinity-Distance Guarantees

    Oren Mangoubi, Nisheeth Vishnoi p12633-12646 from Advances in Neural Information Processing Systems 35
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  • Sampling from Structured Log-Concave Distributions via a Soft-Threshold Dikin Walk

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Sampling from Structured Log-Concave Distributions via a Soft-Threshold Dikin Walk

    Oren Mangoubi, Nisheeth K. Vishnoi p31908-31942 from Advances in Neural Information Processing Systems 36
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  • Sampling in Constrained Domains with Orthogonal-Space Variational Gradient Descent

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Sampling in Constrained Domains with Orthogonal-Space Variational Gradient Descent

    Qiang Liu, Xin Tong, Ruqi Zhang p37108-37120 from Advances in Neural Information Processing Systems 35
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  • Sampling weights of deep neural networks

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Sampling weights of deep neural networks

    Erik L Bolager, Iryna Burak, Chinmay Datar, Felix Dietrich, Qing Sun p63075-63116 from Advances in Neural Information Processing Systems 36
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  • Sampling with Riemannian Hamiltonian Monte Carlo in a Constrained Space

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Sampling with Riemannian Hamiltonian Monte Carlo in a Constrained Space

    Yunbum Kook, Yin-Tat Lee, Ruoqi Shen, Santosh Vempala p31684-31696 from Advances in Neural Information Processing Systems 35
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  • Sampling Without Replacement Leads to Faster Rates in Finite-Sum Minimax Optimization

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Sampling Without Replacement Leads to Faster Rates in Finite-Sum Minimax Optimization

    Aniket Das, Michael Muehlebach, Bernhard Schölkopf p6749-6762 from Advances in Neural Information Processing Systems 35
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  • SAMRS: Scaling-up Remote Sensing Segmentation Dataset with Segment Anything Model

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    SAMRS: Scaling-up Remote Sensing Segmentation Dataset with Segment Anything Model

    Bo Du, Lin Liu, Dacheng Tao, Di Wang, Minqiang Xu, Jing Zhang, Liangpei Zhang p8815-8827 from Advances in Neural Information Processing Systems 36
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  • SAMURAI: Shape and Material from Unconstrained Real-World Arbitrary Image Collections

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    SAMURAI: Shape and Material from Unconstrained Real-World Arbitrary Image Collections

    Jonathan Barron, Mark Boss, Andreas Engelhardt, Varun Jampani, Abhishek Kar, Hendrik Pa Lensch, Yuanzhen Li, Deqing Sun p26389-26403 from Advances in Neural Information Processing Systems 35
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  • SAND: Smooth imputation of sparse and noisy functional data with Transformer networks

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    SAND: Smooth imputation of sparse and noisy functional data with Transformer networks

    Ju-Sheng Hong, Jonas Mueller, Jane-Ling Wang, Junwen Yao p134024-134042 from Advances in Neural Information Processing Systems 37
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  • SANFlow: Semantic-Aware Normalizing Flow for Anomaly Detection

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    SANFlow: Semantic-Aware Normalizing Flow for Anomaly Detection

    Sungyong Baik, Daehyun Kim, Tae Hyun Kim p75434-75454 from Advances in Neural Information Processing Systems 36
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  • SAPA: Similarity-Aware Point Affiliation for Feature Upsampling

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    SAPA: Similarity-Aware Point Affiliation for Feature Upsampling

    Zhiguo Cao, Hongtao Fu, Wenze Liu, Yuliang Liu, Hao Lu, Zixuan Ye p20889-20901 from Advances in Neural Information Processing Systems 35
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  • SAPD+: An Accelerated Stochastic Method for Nonconvex-Concave Minimax Problems

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    SAPD+: An Accelerated Stochastic Method for Nonconvex-Concave Minimax Problems

    Necdet Serhat Aybat, Mert Gurbuzbalaban, Xuan Zhang p21668-21681 from Advances in Neural Information Processing Systems 35
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