Neural Information Processing Systems Foundation, Inc. (NeurIPS)

  • Learning a Neuron by a Shallow ReLU Network: Dynamics and Implicit Bias for Correlated Inputs

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning a Neuron by a Shallow ReLU Network: Dynamics and Implicit Bias for Correlated Inputs

    Dmitry Chistikov, Matthias Englert, Ranko Lazic p23748-23760 from Advances in Neural Information Processing Systems 36
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  • Learning a Single Neuron Robustly to Distributional Shifts and Adversarial Label Noise

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning a Single Neuron Robustly to Distributional Shifts and Adversarial Label Noise

    Shuyao Li, Sushrut Karmalkar, Ilias Diakonikolas, Jelena Diakonikolas p67383-67421 from Advances in Neural Information Processing Systems 37
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  • Learning Across the Gap: Hybrid Multi-armed Bandits with Heterogeneous Offline and Online Data

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning Across the Gap: Hybrid Multi-armed Bandits with Heterogeneous Offline and Online Data

    Qijia He, Minghan Wang, Xutong Liu, Zhiyong Wang, Fang Kong p22934-22978 from Advances in Neural Information Processing Systems 38
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  • Learning Action and Reasoning-Centric Image Editing from Videos and Simulation

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning Action and Reasoning-Centric Image Editing from Videos and Simulation

    Benno Krojer, Dheeraj Vattikonda, Luis Lara, Varun Jampani, Eva Portelance, Christopher Pal, Siva Reddy p38035-38078 from Advances in Neural Information Processing Systems 37
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  • Learning Active Camera for Multi-Object Navigation

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning Active Camera for Multi-Object Navigation

    Peihao Chen, Dongyu Ji, Kunyang Lin, Weiwen Hu, Wenbing Huang, Thomas Li, Mingkui Tan, Chuang Gan p28670-28682 from Advances in Neural Information Processing Systems 35
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  • Learning Adaptive Tensorial Density Fields for Clean Cryo-ET Reconstruction

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning Adaptive Tensorial Density Fields for Clean Cryo-ET Reconstruction

    Yuanhao Wang, Ramzi Idoughi, Wolfgang Heidrich p72270-72283 from Advances in Neural Information Processing Systems 36
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  • Learning Adversarial Low-rank Markov Decision Processes with Unknown Transition and Full-information Feedback

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning Adversarial Low-rank Markov Decision Processes with Unknown Transition and Full-information Feedback

    Canzhe Zhao, Ruofeng Yang, Baoxiang Wang, Xuezhou Zhang, Shuai Li p59107-59123 from Advances in Neural Information Processing Systems 36
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  • Learning an Actionable Discrete Diffusion Policy via Large-Scale Actionless Video Pre-Training

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning an Actionable Discrete Diffusion Policy via Large-Scale Actionless Video Pre-Training

    Haoran He, Chenjia Bai, Ling Pan, Weinan Zhang, Bin Zhao, Xuelong Li p31124-31153 from Advances in Neural Information Processing Systems 37
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  • Learning and Collusion in Multi-unit Auctions

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning and Collusion in Multi-unit Auctions

    Simina Branzei, Mahsa Derakhshan, Negin Golrezaei, Yanjun Han p22191-22225 from Advances in Neural Information Processing Systems 36
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  • Learning and Covering Sums of Independent Random Variables with Unbounded Support

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning and Covering Sums of Independent Random Variables with Unbounded Support

    Alkis Kalavasis, Konstantinos Stavropoulos, Emmanouil Zampetakis p25185-25197 from Advances in Neural Information Processing Systems 35
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  • Learning and Planning Multi-Agent Tasks via an MoE-based World Model

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning and Planning Multi-Agent Tasks via an MoE-based World Model

    Zijie Zhao, Zhongyue Zhao, Kaixuan Xu, Yuqian Fu, Jiajun Chai, Yuanheng Zhu, Dongbin Zhao p45724-45757 from Advances in Neural Information Processing Systems 38
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  • Learning and processing the ordinal information of temporal sequences in recurrent neural circuits

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning and processing the ordinal information of temporal sequences in recurrent neural circuits

    Xiaolong Zou, Zhikun Chu, Qinghai Guo, Jie Cheng, Bo Ho, Si Wu, Yuanyuan Mi p33999-34020 from Advances in Neural Information Processing Systems 36
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  • Learning and Transferring Sparse Contextual Bigrams with Linear Transformers

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning and Transferring Sparse Contextual Bigrams with Linear Transformers

    Yunwei Ren, Zixuan Wang, Jason Lee p20304-20357 from Advances in Neural Information Processing Systems 37
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  • Learning Articulated Rigid Body Dynamics with Lagrangian Graph Neural Network

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning Articulated Rigid Body Dynamics with Lagrangian Graph Neural Network

    Ravinder Bhattoo, Sayan Ranu, N M Anoop Krishnan p29789-29800 from Advances in Neural Information Processing Systems 35
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  • Learning Audio-Visual Dynamics Using Scene Graphs for Audio Source Separation

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning Audio-Visual Dynamics Using Scene Graphs for Audio Source Separation

    Moitreya Chatterjee, Narendra Ahuja, Anoop Cherian p16975-16988 from Advances in Neural Information Processing Systems 35
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  • Learning Best Combination for Efficient N:M Sparsity

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning Best Combination for Efficient N:M Sparsity

    Yuxin Zhang, Mingbao Lin, Zhihang Lin, Yiting Luo, Ke Li, Fei Chao, Yongjian Wu, Rongrong Ji p941-953 from Advances in Neural Information Processing Systems 35
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  • Learning Better Representations From Less Data For Propositional Satisfiability

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning Better Representations From Less Data For Propositional Satisfiability

    Mohamed Ghanem, Frederik Schmitt, Julian Siber, Bernd Finkbeiner p48347-48370 from Advances in Neural Information Processing Systems 37
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  • Learning better with Dale’s Law: A Spectral Perspective

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning better with Dale’s Law: A Spectral Perspective

    Pingsheng Li, Jonathan Cornford, Arna Ghosh, Blake Richards p944-956 from Advances in Neural Information Processing Systems 36
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  • Learning Better with Less: Effective Augmentation for Sample-Efficient Visual Reinforcement Learning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning Better with Less: Effective Augmentation for Sample-Efficient Visual Reinforcement Learning

    Guozheng Ma, Linrui Zhang, Haoyu Wang, Lu Li, Zilin Wang, Zhen Wang, Li Shen, Xueqian Wang, Dacheng Tao p59832-59859 from Advances in Neural Information Processing Systems 36
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  • Learning Bipartite Graphs: Heavy Tails and Multiple Components

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning Bipartite Graphs: Heavy Tails and Multiple Components

    José Vinícius De Miranda Cardoso, Jiaxi Ying, Daniel Palomar p14044-14057 from Advances in Neural Information Processing Systems 35
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  • Learning Bregman Divergences with Application to Robustness

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning Bregman Divergences with Application to Robustness

    Mohamed-Hicham Leghettas, Markus Püschel p131704-131731 from Advances in Neural Information Processing Systems 37
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  • Learning CAD Modeling Sequences via Projection and Part Awareness

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning CAD Modeling Sequences via Projection and Part Awareness

    Yang Liu, Daxuan Ren, Yijie Ding, Jianmin Zheng, Fang Deng p108898-108930 from Advances in Neural Information Processing Systems 38
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  • Learning Causal Models under Independent Changes

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning Causal Models under Independent Changes

    Sarah Mameche, David Kaltenpoth, Jilles Vreeken p75595-75622 from Advances in Neural Information Processing Systems 36
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  • Learning Causally Invariant Representations for Out-Of-Distribution Generalization on Graphs

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning Causally Invariant Representations for Out-Of-Distribution Generalization on Graphs

    Yongqiang Chen, Yonggang Zhang, Yatao Bian, Han Yang, Ma Kaili, Binghui Xie, Tongliang Liu, Bo Han, James Cheng p22131-22148 from Advances in Neural Information Processing Systems 35
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