Paper

  • On the Connection between Pre-training Data Diversity and Fine-tuning Robustness

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    On the Connection between Pre-training Data Diversity and Fine-tuning Robustness

    Vivek Ramanujan, Thao Nguyen, Sewoong Oh, Ali Farhadi, Ludwig Schmidt p66426-66437 from Advances in Neural Information Processing Systems 36
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  • On the Consistency of Maximum Likelihood Estimation of Probabilistic Principal Component Analysis

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    On the Consistency of Maximum Likelihood Estimation of Probabilistic Principal Component Analysis

    Arghya Datta, Sayak Chakrabarty p28648-28662 from Advances in Neural Information Processing Systems 36
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  • On the Consistent Estimation of Optimal Receiver Operating Characteristic (ROC) Curve

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    On the Consistent Estimation of Optimal Receiver Operating Characteristic (ROC) Curve

    Renxiong Liu, Yunzhang Zhu p30720-30731 from Advances in Neural Information Processing Systems 35
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  • On the Constrained Time-Series Generation Problem

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    On the Constrained Time-Series Generation Problem

    Andrea Coletta, Sriram Gopalakrishnan, Daniel Borrajo, Svitlana Vyetrenko p61048-61059 from Advances in Neural Information Processing Systems 36
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  • On the Convergence and Sample Complexity Analysis of Deep Q-Networks with $\epsilon$-Greedy Exploration

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    On the Convergence and Sample Complexity Analysis of Deep Q-Networks with $\epsilon$-Greedy Exploration

    Shuai Zhang, Hongkang Li, Meng Wang, Miao Liu, Pin-Yu Chen, Songtao Lu, Sijia Liu, Keerthiram Murugesan, Subhajit Chaudhury p13064-13102 from Advances in Neural Information Processing Systems 36
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  • On the Convergence of Black-Box Variational Inference

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    On the Convergence of Black-Box Variational Inference

    Kyurae Kim, Jisu Oh, Kaiwen Wu, Yian Ma, Jacob Gardner p44615-44657 from Advances in Neural Information Processing Systems 36
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  • On the Convergence of CART under Sufficient Impurity Decrease Condition

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    On the Convergence of CART under Sufficient Impurity Decrease Condition

    Rahul Mazumder, Haoyue Wang p57754-57782 from Advances in Neural Information Processing Systems 36
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  • On the Convergence of Encoder-only Shallow Transformers

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    On the Convergence of Encoder-only Shallow Transformers

    Yongtao Wu, Fanghui Liu, Grigorios Chrysos, Volkan Cevher p52197-52237 from Advances in Neural Information Processing Systems 36
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  • On the Convergence of Loss and Uncertainty-based Active Learning Algorithms

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    On the Convergence of Loss and Uncertainty-based Active Learning Algorithms

    Daniel Haimovich, Dima Karamshuk, Fridolin Linder, Niek Tax, Milan Vojnovic p122770-122810 from Advances in Neural Information Processing Systems 37
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  • On the Convergence of No-Regret Learning Dynamics in Time-Varying Games

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    On the Convergence of No-Regret Learning Dynamics in Time-Varying Games

    Ioannis Anagnostides, Ioannis Panageas, Gabriele Farina, Tuomas Sandholm p16367-16405 from Advances in Neural Information Processing Systems 36
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  • On the Convergence of Policy Gradient Methods to Nash Equilibria in General Stochastic Games

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    On the Convergence of Policy Gradient Methods to Nash Equilibria in General Stochastic Games

    Angeliki Giannou, Kyriakos Lotidis, Panayotis Mertikopoulos, Emmanouil-Vasileios Vlatakis-Gkaragkounis p7128-7141 from Advances in Neural Information Processing Systems 35
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  • On the Convergence of Stochastic Multi-Objective Gradient Manipulation and Beyond

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    On the Convergence of Stochastic Multi-Objective Gradient Manipulation and Beyond

    Shiji Zhou, Wenpeng Zhang, Jiyan Jiang, Wenliang Zhong, Jinjie Gu, Wenwu Zhu p38103-38115 from Advances in Neural Information Processing Systems 35
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