Neural Information Processing Systems Foundation, Inc. (NeurIPS)

  • Model Decides How to Tokenize: Adaptive DNA Sequence Tokenization with MxDNA

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Model Decides How to Tokenize: Adaptive DNA Sequence Tokenization with MxDNA

    Weiqiang Bai, Nanqing Dong, Chaoqi Liang, Xinzhu Ma, Wanli Ouyang, Lifeng Qiao, Yuchen Ren, Peng Ye p66080-66107 from Advances in Neural Information Processing Systems 37
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  • Model Fusion through Bayesian Optimization in Language Model Fine-Tuning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Model Fusion through Bayesian Optimization in Language Model Fine-Tuning

    Chaeyun Jang, Jungtaek Kim, Hyungi Lee, Juho Lee p29878-29912 from Advances in Neural Information Processing Systems 37
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  • Model LEGO: Creating Models Like Disassembling and Assembling Building Blocks

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Model LEGO: Creating Models Like Disassembling and Assembling Building Blocks

    Zunlei Feng, Jing Gao, Yang Gao, Jiacong Hu, Mingli Song, Xingen Wang, Jingwen Ye p127711-127738 from Advances in Neural Information Processing Systems 37
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  • Model Preserving Compression for Neural Networks

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Model Preserving Compression for Neural Networks

    Jerry Chee, Anil Damle, Christopher De Sa, Megan Flynn Née Renz p38060-38074 from Advances in Neural Information Processing Systems 35
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  • Model Reconstruction Using Counterfactual Explanations: A Perspective From Polytope Theory

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Model Reconstruction Using Counterfactual Explanations: A Perspective From Polytope Theory

    Pasan Dissanayake, Sanghamitra Dutta p83397-83429 from Advances in Neural Information Processing Systems 37
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  • Model Sensitivity Aware Continual Learning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Model Sensitivity Aware Continual Learning

    Heng Huang, Zhenyi Wang p132583-132613 from Advances in Neural Information Processing Systems 37
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  • Model Shapley: Equitable Model Valuation with Black-box Access

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Model Shapley: Equitable Model Valuation with Black-box Access

    Chuan Sheng Foo, Thanh Lam, Bryan Kian Hsiang Low, Xinyi Xu p43254-43283 from Advances in Neural Information Processing Systems 36
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  • Model Sparsity Can Simplify Machine Unlearning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Model Sparsity Can Simplify Machine Unlearning

    Jinghan Jia, Gaowen Liu, Jiancheng Liu, Sijia Liu, Yang Liu, Parikshit Ram, Pranay Sharma, Yuguang Yao p51584-51605 from Advances in Neural Information Processing Systems 36
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  • Model Spider: Learning to Rank Pre-Trained Models Efficiently

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Model Spider: Learning to Rank Pre-Trained Models Efficiently

    Yao-Xiang Ding, Ting-Ji Huang, Han-Jia Ye, De-Chuan Zhan, Yi-Kai Zhang p13692-13719 from Advances in Neural Information Processing Systems 36
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  • Model Zoos: A Dataset of Diverse Populations of Neural Network Models

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Model Zoos: A Dataset of Diverse Populations of Neural Network Models

    Damian Borth, Xavier Giró-I-Nieto, Boris Knyazev, Konstantin Schürholt, Diyar Taskiran p38134-38148 from Advances in Neural Information Processing Systems 35
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  • Model-Based Control with Sparse Neural Dynamics

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Model-Based Control with Sparse Neural Dynamics

    Jeff He, Fei-Fei Li, Yunzhu Li, Ziang Liu, Tobia Marcucci, Jiajun Wu, Genggeng Zhou p6280-6296 from Advances in Neural Information Processing Systems 36
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  • Model-based Diffusion for Trajectory Optimization

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Model-based Diffusion for Trajectory Optimization

    Chaoyi Pan, Guannan Qu, Guanya Shi, Zeji Yi p57914-57943 from Advances in Neural Information Processing Systems 37
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  • Model-Based Imitation Learning for Urban Driving

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Model-Based Imitation Learning for Urban Driving

    Roberto Cipolla, Gianluca Corrado, Nicolas Griffiths, Corina Gurau, Anthony Hu, Alex Kendall, Zachary Murez, Jamie Shotton, Hudson Yeo p20703-20716 from Advances in Neural Information Processing Systems 35
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  • Model-Based Lifelong Reinforcement Learning with Bayesian Exploration

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Model-Based Lifelong Reinforcement Learning with Bayesian Exploration

    Haotian Fu, George Konidaris, Michael Littman, Shangqun Yu p32369-32382 from Advances in Neural Information Processing Systems 35
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  • Model-Based Offline Reinforcement Learning with Pessimism-Modulated Dynamics Belief

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Model-Based Offline Reinforcement Learning with Pessimism-Modulated Dynamics Belief

    Yanhui Geng, Kaiyang Guo, Shao Yunfeng p449-461 from Advances in Neural Information Processing Systems 35
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  • Model-Based Opponent Modeling

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Model-Based Opponent Modeling

    Haobin Jiang, Jiechuan Jiang, Zongqing Lu, Xiaopeng Yu, Wanpeng Zhang p28208-28221 from Advances in Neural Information Processing Systems 35
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  • Model-Based Reparameterization Policy Gradient Methods: Theory and Practical Algorithms

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Model-Based Reparameterization Policy Gradient Methods: Theory and Practical Algorithms

    Boyi Liu, Zhaoran Wang, Shenao Zhang, Tuo Zhao p68391-68419 from Advances in Neural Information Processing Systems 36
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  • Model-Based RL with Optimistic Posterior Sampling: Structural Conditions and Sample Complexity

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Model-Based RL with Optimistic Posterior Sampling: Structural Conditions and Sample Complexity

    Alekh Agarwal, Tong Zhang p35284-35297 from Advances in Neural Information Processing Systems 35
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  • Model-Based Safe Deep Reinforcement Learning Via a Constrained Proximal Policy Optimization Algorithm

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Model-Based Safe Deep Reinforcement Learning Via a Constrained Proximal Policy Optimization Algorithm

    Shalabh Bhatnagar, Ashish K Jayant p24432-24445 from Advances in Neural Information Processing Systems 35
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  • Model-Based Transfer Learning for Contextual Reinforcement Learning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Model-Based Transfer Learning for Contextual Reinforcement Learning

    Jung-Hoon Cho, Vindula Jayawardana, Sirui Li, Cathy Wu p88279-88319 from Advances in Neural Information Processing Systems 37
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  • Model-enhanced Vector Index

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Model-enhanced Vector Index

    Ruiheng Chang, Qi Chen, Bin Cui, Weiwei Deng, Yang Ding, Yingyan Hou, Xupeng Miao, Ziming Miao, Bochen Pang, Hao Sun, Haonan Wang, Yujing Wang, Xing Xie, Fan Yang, Mao Yang, Yuefeng Zhan, Qi Zhang, Hailin Zhang, Ting Zhang p54903-54917 from Advances in Neural Information Processing Systems 36
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  • Model-Free Active Exploration in Reinforcement Learning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Model-Free Active Exploration in Reinforcement Learning

    Alexandre Proutiere, Alessio Russo p54740-54753 from Advances in Neural Information Processing Systems 36
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  • Model-free Low-Rank Reinforcement Learning via Leveraged Entry-wise Matrix Estimation

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Model-free Low-Rank Reinforcement Learning via Leveraged Entry-wise Matrix Estimation

    Yassir Jedra, Alexandre Proutiere, Stefan Stojanovic p30886-30924 from Advances in Neural Information Processing Systems 37
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  • Model-free Posterior Sampling via Learning Rate Randomization

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Model-free Posterior Sampling via Learning Rate Randomization

    Denis Belomestny, Daniele Calandriello, Pierre Ménard, Eric Moulines, Remi Munos, Alexey Naumov, Pierre Perrault, Daniil Tiapkin, Michal Valko p73719-73774 from Advances in Neural Information Processing Systems 36
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