Neural Information Processing Systems Foundation, Inc. (NeurIPS)

  • On the Power of SVD in the Stochastic Block Model

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    On the Power of SVD in the Stochastic Block Model

    Xinyu Mao, Jiapeng Zhang p32765-32781 from Advances in Neural Information Processing Systems 36
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  • On the Powerfulness of Textual Outlier Exposure for Visual OoD Detection

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    On the Powerfulness of Textual Outlier Exposure for Visual OoD Detection

    Dahuin Jung, Saehyung Lee, Jisoo Mok, Sangha Park, Sungroh Yoon p51675-51687 from Advances in Neural Information Processing Systems 36
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  • On the Properties of Kullback-Leibler Divergence Between Multivariate Gaussian Distributions

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    On the Properties of Kullback-Leibler Divergence Between Multivariate Gaussian Distributions

    Zhenbang Chen, Li Ken Li, Wanwei Liu, Xinwang Liu, Jialu Pan, J Wang, Yufeng Zhang p58152-58165 from Advances in Neural Information Processing Systems 36
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  • On the Relationship Between Relevance and Conflict in Online Social Link Recommendations

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    On the Relationship Between Relevance and Conflict in Online Social Link Recommendations

    Jon Kleinberg, Yanbang Wang p36708-36725 from Advances in Neural Information Processing Systems 36
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  • On the Relationship Between Variational Inference and Auto-Associative Memory

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    On the Relationship Between Variational Inference and Auto-Associative Memory

    Louis Annabi, Alexandre Pitti, Mathias Quoy p37497-37509 from Advances in Neural Information Processing Systems 35
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  • On the Representation Collapse of Sparse Mixture of Experts

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    On the Representation Collapse of Sparse Mixture of Experts

    Payal Bajaj, Zewen Chi, Damai Dai, Li Dong, Heyan Huang, Shaohan Huang, Shuming Ma, Xian-Ling Mao, Barun Patra, Saksham Singhal, Xia Song, Furu Wei p34600-34613 from Advances in Neural Information Processing Systems 35
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  • On the Robustness of Deep Clustering Models: Adversarial Attacks and Defenses

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    On the Robustness of Deep Clustering Models: Adversarial Attacks and Defenses

    Anshuman Chhabra, Prasant Mohapatra, Ashwin Sekhari p20566-20579 from Advances in Neural Information Processing Systems 35
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  • On the Robustness of Graph Neural Diffusion to Topology Perturbations

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    On the Robustness of Graph Neural Diffusion to Topology Perturbations

    Qiyu Kang, Yang Song, Wee Peng Tay, Sijie Wang, Kai Zhao p6384-6396 from Advances in Neural Information Processing Systems 35
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  • On the Robustness of Mechanism Design under Total Variation Distance

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    On the Robustness of Mechanism Design under Total Variation Distance

    Anuran Makur, Marios Mertzanidis, Alexandros Psomas, Athina Terzoglou p1620-1629 from Advances in Neural Information Processing Systems 36
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  • On the Robustness of Removal-Based Feature Attributions

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    On the Robustness of Removal-Based Feature Attributions

    Ian Covert, Su-In Lee, Chris Lin p79613-79666 from Advances in Neural Information Processing Systems 36
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  • On the Robustness of Spectral Algorithms for Semirandom Stochastic Block Models

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    On the Robustness of Spectral Algorithms for Semirandom Stochastic Block Models

    Aditya Bhaskara, Agastya Jha, Michael Kapralov, Naren Manoj, Davide Mazzali, Weronika Wrzos-Kaminska p112731-112776 from Advances in Neural Information Processing Systems 37
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  • On the Role of Attention Masks and LayerNorm in Transformers

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    On the Role of Attention Masks and LayerNorm in Transformers

    Amir Ajorlou, Ali Jadbabaie, Stefanie Jegelka, Yifei Wang, Xinyi Wu p14774-14809 from Advances in Neural Information Processing Systems 37
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  • On the Role of Entanglement and Statistics in Learning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    On the Role of Entanglement and Statistics in Learning

    Srinivasan Arunachalam, Vojtech Havlicek, Louis Schatzki p55064-55076 from Advances in Neural Information Processing Systems 36
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  • On the Role of Information Structure in Reinforcement Learning for Partially-Observable Sequential Teams and Games

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    On the Role of Information Structure in Reinforcement Learning for Partially-Observable Sequential Teams and Games

    Awni Altabaa, Zhuoran Yang p6648-6710 from Advances in Neural Information Processing Systems 37
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  • On the Role of Noise in the Sample Complexity of Learning Recurrent Neural Networks: Exponential Gaps for Long Sequences

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    On the Role of Noise in the Sample Complexity of Learning Recurrent Neural Networks: Exponential Gaps for Long Sequences

    Hassan Ashtiani, Alireza F. Pour p80257-80269 from Advances in Neural Information Processing Systems 36
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  • On the Role of Overparameterization in Off-Policy Temporal Difference Learning with Linear Function Approximation

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    On the Role of Overparameterization in Off-Policy Temporal Difference Learning with Linear Function Approximation

    Valentin Thomas p37228-37240 from Advances in Neural Information Processing Systems 35
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  • On the Role of Randomization in Adversarially Robust Classification

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    On the Role of Randomization in Adversarially Robust Classification

    Yann Chevaleyre, Lucas Gnecco Heredia, Laurent Meunier, Benjamin Negrevergne, Muni Sreenivas Pydi p79293-79319 from Advances in Neural Information Processing Systems 36
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  • On the Safety of Interpretable Machine Learning: A Maximum Deviation Approach

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    On the Safety of Interpretable Machine Learning: A Maximum Deviation Approach

    Elizabeth Daly, Amit Dhurandhar, Rahul Nair, Moninder Singh, Kush Varshney, Dennis Wei p9866-9880 from Advances in Neural Information Processing Systems 35
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  • On the Sample Complexity of Stabilizing LTI Systems on a Single Trajectory

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    On the Sample Complexity of Stabilizing LTI Systems on a Single Trajectory

    Yang Hu, Guannan Qu, Adam Wierman p16989-17002 from Advances in Neural Information Processing Systems 35
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  • On the Saturation Effects of Spectral Algorithms in Large Dimensions

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    On the Saturation Effects of Spectral Algorithms in Large Dimensions

    Yicheng Li, Qian Lin, Weihao Lu, Haobo Zhang p7011-7059 from Advances in Neural Information Processing Systems 37
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  • On the Scalability of Certified Adversarial Robustness with Generated Data

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    On the Scalability of Certified Adversarial Robustness with Generated Data

    Thomas Altstidl, David Dobre, Björn Eskofier, Gauthier Gidel, Arthur Kosmala, Leo Schwinn p102255-102278 from Advances in Neural Information Processing Systems 37
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  • On the Scalability of GNNs for Molecular Graphs

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    On the Scalability of GNNs for Molecular Graphs

    Dominique Beaini, Nia Dickson, Philip Fradkin, Farimah Poursafaei, Karush Suri, Maciej Sypetkowski, Frederik Wenkel p19870-19906 from Advances in Neural Information Processing Systems 37
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  • On the SDEs and Scaling Rules for Adaptive Gradient Algorithms

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    On the SDEs and Scaling Rules for Adaptive Gradient Algorithms

    Sanjeev Arora, Kaifeng Lyu, Sadhika Malladi, Abhishek Panigrahi p7697-7711 from Advances in Neural Information Processing Systems 35
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  • On the Size and Approximation Error of Distilled Datasets

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    On the Size and Approximation Error of Distilled Datasets

    Ramin Hasani, Mathias Lechner, Noel Loo, Alaa Maalouf, Daniela Rus, Murad Tukan p61085-61102 from Advances in Neural Information Processing Systems 36
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