Paper

  • Beyond Exponential Graph: Communication-Efficient Topologies for Decentralized Learning via Finite-time Convergence

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Beyond Exponential Graph: Communication-Efficient Topologies for Decentralized Learning via Finite-time Convergence

    Han Bao, Kenta Niwa, Ryoma Sato, Yuki Takezawa, Makoto Yamada p76692-76717 from Advances in Neural Information Processing Systems 36
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  • Beyond Geometry: Comparing the Temporal Structure of Computation in Neural Circuits with Dynamical Similarity Analysis

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Beyond Geometry: Comparing the Temporal Structure of Computation in Neural Circuits with Dynamical Similarity Analysis

    Adam Eisen, Ila Fiete, Leo Kozachkov, Mitchell Ostrow p33824-33837 from Advances in Neural Information Processing Systems 36
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  • Beyond IID: Data-Driven Decision-Making in Heterogeneous Environments

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Beyond IID: Data-Driven Decision-Making in Heterogeneous Environments

    Omar Besbes, Will Ma, Omar Mouchtaki p23979-23991 from Advances in Neural Information Processing Systems 35
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  • Beyond Invariance: Test-Time Label-Shift Adaptation for Addressing "Spurious" Correlations

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Beyond Invariance: Test-Time Label-Shift Adaptation for Addressing "Spurious" Correlations

    Alexander D'Amour, Sayna Ebrahimi, Kevin Murphy, Qingyao Sun p23789-23812 from Advances in Neural Information Processing Systems 36
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  • Beyond L1: Faster and Better Sparse Models with Skglm

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Beyond L1: Faster and Better Sparse Models with Skglm

    Pierre-Antoine Bannier, Quentin Bertrand, Gauthier Gidel, Quentin Klopfenstein, Mathurin Massias p38950-38965 from Advances in Neural Information Processing Systems 35
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  • Beyond Mahalanobis Distance for Textual OOD Detection

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Beyond Mahalanobis Distance for Textual OOD Detection

    Pierre Colombo, Eduardo Dadalto, Nathan Noiry, Pablo Piantanida, Guillaume Staerman p17744-17759 from Advances in Neural Information Processing Systems 35
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  • Beyond MLE: Convex Learning for Text Generation

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Beyond MLE: Convex Learning for Text Generation

    Yang Feng, Zhengrui Ma, Chenze Shao, Min Zhang p8913-8936 from Advances in Neural Information Processing Systems 36
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  • Beyond Myopia: Learning from Positive and Unlabeled Data through Holistic Predictive Trends

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Beyond Myopia: Learning from Positive and Unlabeled Data through Holistic Predictive Trends

    Songcan Chen, Chuanxing Geng, Shao-Yuan Li, Wenhai Wan, Wang Xinrui p67589-67602 from Advances in Neural Information Processing Systems 36
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  • Beyond Neural Scaling Laws: Beating Power Law Scaling Via Data Pruning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Beyond Neural Scaling Laws: Beating Power Law Scaling Via Data Pruning

    Surya Ganguli, Robert Geirhos, Ari Morcos, Shashank Shekhar, Ben Sorscher p19523-19536 from Advances in Neural Information Processing Systems 35
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  • Beyond Normal: On the Evaluation of Mutual Information Estimators

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Beyond Normal: On the Evaluation of Mutual Information Estimators

    Niko Beerenwinkel, Pawel Czyz, Frederic Grabowski, Alexander Marx, Julia Vogt p16957-16990 from Advances in Neural Information Processing Systems 36
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  • Beyond Not-Forgetting: Continual Learning with Backward Knowledge Transfer

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Beyond Not-Forgetting: Continual Learning with Backward Knowledge Transfer

    Deliang Fan, Sen Lin, Li Yang, Junshan Zhang p16165-16177 from Advances in Neural Information Processing Systems 35
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  • Beyond NTK with Vanilla Gradient Descent: A Mean-Field Analysis of Neural Networks with Polynomial Width, Samples, and Time

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Beyond NTK with Vanilla Gradient Descent: A Mean-Field Analysis of Neural Networks with Polynomial Width, Samples, and Time

    Kefan Dong, Margalit Glasgow, Tengyu Ma, Arvind Mahankali, Haochen Zhang p57367-57480 from Advances in Neural Information Processing Systems 36
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