Paper

  • A Unified Approach for Maximizing Continuous DR-submodular Functions

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    A Unified Approach for Maximizing Continuous DR-submodular Functions

    Vaneet Aggarwal, Mohammad Pedramfar, Christopher Quinn p61103-61114 from Advances in Neural Information Processing Systems 36
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  • A Unified Approach to Count-Based Weakly Supervised Learning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    A Unified Approach to Count-Based Weakly Supervised Learning

    Kareem Ahmed, Vinay Shukla, Guy Van Den Broeck, Zhe Zeng p38709-38722 from Advances in Neural Information Processing Systems 36
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  • A Unified Approach to Domain Incremental Learning with Memory: Theory and Algorithm

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    A Unified Approach to Domain Incremental Learning with Memory: Theory and Algorithm

    Haizhou Shi, Hao Wang p15027-15059 from Advances in Neural Information Processing Systems 36
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  • A Unified Conditional Framework for Diffusion-based Image Restoration

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    A Unified Conditional Framework for Diffusion-based Image Restoration

    Dasong Li, Hongsheng Li, Xiaoyu Shi, Xiaogang Wang, Jian Wang, Yi Zhang p49703-49714 from Advances in Neural Information Processing Systems 36
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  • A Unified Confidence Sequence for Generalized Linear Models, with Applications to Bandits

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    A Unified Confidence Sequence for Generalized Linear Models, with Applications to Bandits

    Kwang-Sung Jun, Jungyhun Lee, Se-Young Yun p124640-124685 from Advances in Neural Information Processing Systems 37
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  • A Unified Convergence Theorem for Stochastic Optimization Methods

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    A Unified Convergence Theorem for Stochastic Optimization Methods

    Xiao Li, Andre Milzarek p33107-33119 from Advances in Neural Information Processing Systems 35
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  • A Unified Debiasing Approach for Vision-Language Models across Modalities and Tasks

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    A Unified Debiasing Approach for Vision-Language Models across Modalities and Tasks

    Taeuk Jang, Hoin Jung, Xiaoqian Wang p21034-21058 from Advances in Neural Information Processing Systems 37
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  • A Unified Detection Framework for Inference-Stage Backdoor Defenses

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    A Unified Detection Framework for Inference-Stage Backdoor Defenses

    Xuan Bi, Jie Ding, Mingyi Hong, Ashish Kundu, Jayanth Srinivasa, Ganghua Wang, Xun Xian p7867-7894 from Advances in Neural Information Processing Systems 36
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  • A Unified Discretization Framework for Differential Equation Approach with Lyapunov Arguments for Convex Optimization

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    A Unified Discretization Framework for Differential Equation Approach with Lyapunov Arguments for Convex Optimization

    Takayasu Matsuo, Shun Sato, Kansei Ushiyama p26092-26120 from Advances in Neural Information Processing Systems 36
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  • A Unified Diversity Measure for Multiagent Reinforcement Learning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    A Unified Diversity Measure for Multiagent Reinforcement Learning

    Yuan Li, Zongkai Liu, Peng Sun, Zifan Wu, Yaodong Yang, Chao Yu p10339-10352 from Advances in Neural Information Processing Systems 35
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  • A Unified Evaluation of Textual Backdoor Learning: Frameworks and Benchmarks

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    A Unified Evaluation of Textual Backdoor Learning: Frameworks and Benchmarks

    Yangyi Chen, Ganqu Cui, Bingxiang He, Zhiyuan Liu, Maosong Sun, Lifan Yuan p5009-5023 from Advances in Neural Information Processing Systems 35
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  • A Unified Fast Gradient Clipping Framework for DP-SGD

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    A Unified Fast Gradient Clipping Framework for DP-SGD

    Weiwei Kong, Andres Munoz Medina p52401-52412 from Advances in Neural Information Processing Systems 36
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