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, Begoña García Malaxechebarría, Andrew W. Mackenzie, Courtney Paquette, Elliot Paquette, Inbar Seroussi 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

    Benoit Dherin, Javier Gonzalvo, Michael Munn 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

    Nikhil Ghosh, Soufiane Hayou, 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

    Payel Das, Amirhossein Kazemnejad, Karthikeyan Natesan Ramamurthy, Inkit Padhi, 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, Sirui Li, Dajiang Suo, Catherine Tang, 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

    Yuan Cao, Chenyang Zhang, Difan Zou 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

    Geyong Min, Wenjie Ruan, Zheng Wang 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

    Cong Fang, Yihong Gu, Yang Xu 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

    Aditi Krishnapriyan, Eric Qu 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

    J. Bagnell, Aarti Singh, Yuda Song, Wen Sun, Gokul Swamy 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, Subhransu Maji, Alexander Shepard, 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, Ran Gilad-Bachrach, Amir Globerson 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

    Dan Alistarh, Denis Kuznedelev, Ionut-Vlad Modoranu, Mher Safaryan, Diyuan Wu 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

    Chen Chen, Jianye Hao, Hongyao Tang, Min Zhang 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

    Yoav Levine, Amnon Shashua, Noam Wies 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

    Seijin Kobayashi, Alexander Meulemans, João Sacramento, Johannes Von Oswald, Nicolas Zucchet 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

    Yudong Chen, Tyler Sam, 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

    Tri Dao, Avner May, Daniele Paliotta, Alexander Rush, Junxiong Wang 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

    Kasper Green Larsen, Markus Engelund Mathiasen, Mikael Møller Høgsgaard 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, Ingo Scholtes, Chester Tan p17428-17456 from Advances in Neural Information Processing Systems 37
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