Neural Information Processing Systems Foundation, Inc. (NeurIPS)

  • The Hessian Screening Rule

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    The Hessian Screening Rule

    Johan Larsson, Jonas Wallin p15823-15835 from Advances in Neural Information Processing Systems 35
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  • The High Line: Exact Risk and Learning Rate Curves of Stochastic Adaptive Learning Rate Algorithms

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    The High Line: Exact Risk and Learning Rate Curves of Stochastic Adaptive Learning Rate Algorithms

    Elizabeth Collins-Woodfin, Inbar Seroussi, Begoña García Malaxechebarría, Andrew W. Mackenzie, Elliot Paquette, Courtney Paquette p6500-6548 from Advances in Neural Information Processing Systems 37
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  • The Impact of Geometric Complexity on Neural Collapse in Transfer Learning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    The Impact of Geometric Complexity on Neural Collapse in Transfer Learning

    Michael Munn, Benoit Dherin, Javier Gonzalvo p66713-66742 from Advances in Neural Information Processing Systems 37
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  • The Impact of Initialization on LoRA Finetuning Dynamics

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    The Impact of Initialization on LoRA Finetuning Dynamics

    Soufiane Hayou, Nikhil Ghosh, Bin Yu p117015-117040 from Advances in Neural Information Processing Systems 37
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  • The Impact of Positional Encoding on Length Generalization in Transformers

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    The Impact of Positional Encoding on Length Generalization in Transformers

    Amirhossein Kazemnejad, Inkit Padhi, Karthikeyan Natesan Ramamurthy, Payel Das, Siva Reddy p24892-24928 from Advances in Neural Information Processing Systems 36
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  • The Impact of Task Underspecification in Evaluating Deep Reinforcement Learning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    The Impact of Task Underspecification in Evaluating Deep Reinforcement Learning

    Vindula Jayawardana, Catherine Tang, Sirui Li, Dajiang Suo, Cathy Wu p23881-23893 from Advances in Neural Information Processing Systems 35
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  • The Implicit Bias of Adam on Separable Data

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    The Implicit Bias of Adam on Separable Data

    Chenyang Zhang, Difan Zou, Yuan Cao p23988-24021 from Advances in Neural Information Processing Systems 37
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  • The Implicit Bias of Gradient Descent on Separable Multiclass Data

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    The Implicit Bias of Gradient Descent on Separable Multiclass Data

    Hrithik Ravi, Clayton Scott, Daniel Soudry, Yutong Wang p81324-81359 from Advances in Neural Information Processing Systems 37
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  • The Implicit Bias of Gradient Descent toward Collaboration between Layers: A Dynamic Analysis of Multilayer Perceptions

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    The Implicit Bias of Gradient Descent toward Collaboration between Layers: A Dynamic Analysis of Multilayer Perceptions

    Zheng Wang, Geyong Min, Wenjie Ruan p74868-74898 from Advances in Neural Information Processing Systems 37
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  • The Implicit Bias of Heterogeneity towards Invariance: A Study of Multi-Environment Matrix Sensing

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    The Implicit Bias of Heterogeneity towards Invariance: A Study of Multi-Environment Matrix Sensing

    Yang Xu, Yihong Gu, Cong Fang p14864-14902 from Advances in Neural Information Processing Systems 37
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  • The Implicit Delta Method

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    The Implicit Delta Method

    Nathan Kallus, James McInerney p37471-37483 from Advances in Neural Information Processing Systems 35
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  • The Importance of Being Scalable: Improving the Speed and Accuracy of Neural Network Interatomic Potentials Across Chemical Domains

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    The Importance of Being Scalable: Improving the Speed and Accuracy of Neural Network Interatomic Potentials Across Chemical Domains

    Eric Qu, Aditi Krishnapriyan p139030-139053 from Advances in Neural Information Processing Systems 37
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  • The Importance of Online Data: Understanding Preference Fine-tuning via Coverage

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    The Importance of Online Data: Understanding Preference Fine-tuning via Coverage

    Yuda Song, Gokul Swamy, Aarti Singh, J. Bagnell, Wen Sun p12243-12270 from Advances in Neural Information Processing Systems 37
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  • The iNaturalist Sounds Dataset

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    The iNaturalist Sounds Dataset

    Mustafa Chasmai, Alexander Shepard, Subhransu Maji, Grant Van Horn p132524-132544 from Advances in Neural Information Processing Systems 37
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  • The Intelligible and Effective Graph Neural Additive Network

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    The Intelligible and Effective Graph Neural Additive Network

    Maya Bechler-Speicher, Amir Globerson, Ran Gilad-Bachrach p90552-90578 from Advances in Neural Information Processing Systems 37
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  • The Iterative Optimal Brain Surgeon: Faster Sparse Recovery by Leveraging Second-Order Information

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    The Iterative Optimal Brain Surgeon: Faster Sparse Recovery by Leveraging Second-Order Information

    Diyuan Wu, Ionut-Vlad Modoranu, Mher Safaryan, Denis Kuznedelev, Dan Alistarh p139621-139649 from Advances in Neural Information Processing Systems 37
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  • The Ladder in Chaos: Improving Policy Learning by Harnessing the Parameter Evolving Path in A Low-dimensional Space

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    The Ladder in Chaos: Improving Policy Learning by Harnessing the Parameter Evolving Path in A Low-dimensional Space

    Hongyao Tang, Min Zhang, Chen Chen, Jianye Hao p71004-71033 from Advances in Neural Information Processing Systems 37
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  • The Learnability of In-Context Learning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    The Learnability of In-Context Learning

    Noam Wies, Yoav Levine, Amnon Shashua p36637-36651 from Advances in Neural Information Processing Systems 36
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  • The Least-Control Principle for Local Learning at Equilibrium

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    The Least-Control Principle for Local Learning at Equilibrium

    Alexander Meulemans, Nicolas Zucchet, Seijin Kobayashi, Johannes Von Oswald, João Sacramento p33603-33617 from Advances in Neural Information Processing Systems 35
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  • The Limits of Differential Privacy in Online Learning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    The Limits of Differential Privacy in Online Learning

    Bo Li, Wei Wang, Peng Ye p65328-65360 from Advances in Neural Information Processing Systems 37
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  • The Limits of Transfer Reinforcement Learning with Latent Low-rank Structure

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    The Limits of Transfer Reinforcement Learning with Latent Low-rank Structure

    Tyler Sam, Yudong Chen, Christina Yu p108262-108330 from Advances in Neural Information Processing Systems 37
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  • The Mamba in the Llama: Distilling and Accelerating Hybrid Models

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    The Mamba in the Llama: Distilling and Accelerating Hybrid Models

    Junxiong Wang, Daniele Paliotta, Avner May, Alexander Rush, Tri Dao p62432-62457 from Advances in Neural Information Processing Systems 37
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  • The Many Faces of Optimal Weak-to-Strong Learning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    The Many Faces of Optimal Weak-to-Strong Learning

    Mikael Møller Høgsgaard, Kasper Green Larsen, Markus Engelund Mathiasen p51885-51904 from Advances in Neural Information Processing Systems 37
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  • The Map Equation Goes Neural: Mapping Network Flows with Graph Neural Networks

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    The Map Equation Goes Neural: Mapping Network Flows with Graph Neural Networks

    Christopher Blöcker, Chester Tan, Ingo Scholtes p17428-17456 from Advances in Neural Information Processing Systems 37
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