Neural Information Processing Systems Foundation, Inc. (NeurIPS)

Neural Information Processing Systems Foundation, Inc. (NeurIPS)

RGMDT: Return-Gap-Minimizing Decision Tree Extraction in Non-Euclidean Metric Space

Jingdi Chen, Hanhan Zhou, Yongsheng Mei, Carlee Joe-Wong, Gina Adam, Nathaniel Bastian, Tian Lan p18806-18847 from Advances in Neural Information Processing Systems 37

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RGMIL: Guide Your Multiple-Instance Learning Model with Regressor

Zhaolong Du, Shasha Mao, Yimeng Zhang, Shuiping Gou, Licheng Jiao, Lin Xiong p35606-35618 from Advances in Neural Information Processing Systems 36

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RH-BrainFS: Regional Heterogeneous Multimodal Brain Networks Fusion Strategy

Hongting Ye, Yalu Zheng, Yueying Li, Ke Zhang, Youyong Kong, Yonggui Yuan p59286-59303 from Advances in Neural Information Processing Systems 36

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Richelieu: Self-Evolving LLM-Based Agents for AI Diplomacy

Zhenyu Guan, Xiangyu Kong, Fangwei Zhong, Yizhou Wang p123471-123497 from Advances in Neural Information Processing Systems 37

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Riemannian Diffusion Models

Chin-Wei Huang, Milad Aghajohari, Joey Bose, Prakash Panangaden, Aaron Courville p2750-2761 from Advances in Neural Information Processing Systems 35

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Riemannian Laplace approximations for Bayesian neural networks

Federico Bergamin, Pablo Moreno-Muñoz, Søren Hauberg, Georgios Arvanitidis p31066-31095 from Advances in Neural Information Processing Systems 36

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Riemannian Neural SDE: Learning Stochastic Representations on Manifolds

Sung Woo Park, Hyomin Kim, Kyungjae Lee, Junseok Kwon p1434-1444 from Advances in Neural Information Processing Systems 35

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Riemannian Projection-free Online Learning

Zihao Hu, Guanghui Wang, Jacob Abernethy p41980-42014 from Advances in Neural Information Processing Systems 36

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Riemannian Residual Neural Networks

Isay Katsman, Eric Chen, Sidhanth Holalkere, Anna Asch, Aaron Lou, Ser Nam Lim, Christopher De Sa p63502-63514 from Advances in Neural Information Processing Systems 36

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Riemannian SAM: Sharpness-Aware Minimization on Riemannian Manifolds

Jihun Yun, Eunho Yang p65784-65800 from Advances in Neural Information Processing Systems 36

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Riemannian Score-Based Generative Modelling

Valentin De Bortoli, Emile Mathieu, Michael Hutchinson, James Thornton, Yee Whye Teh, Arnaud Doucet p2406-2422 from Advances in Neural Information Processing Systems 35

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Riemannian stochastic optimization methods avoid strict saddle points

Ya-Ping Hsieh, Mohammad Reza Karimi Jaghargh, Andreas Krause, Panayotis Mertikopoulos p29580-29601 from Advances in Neural Information Processing Systems 36

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Right this way: Can VLMs Guide Us to See More to Answer Questions?

Li Liu, Diji Yang, Sijia Zhong, Kalyana Tholeti, Lei Ding, Yi Zhang, Leilani Gilpin p132946-132976 from Advances in Neural Information Processing Systems 37

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Rigorous Runtime Analysis of MOEA/D for Solving Multi-Objective Minimum Weight Base Problems

Anh Viet Do, Aneta Neumann, Frank Neumann, Andrew Sutton p36434-36448 from Advances in Neural Information Processing Systems 36

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RIO: A Benchmark for Reasoning Intention-Oriented Objects in Open Environments

Mengxue Qu, Yu Wu, Wu Liu, Xiaodan Liang, Jingkuan Song, Yao Zhao, Yunchao Wei p43041-43056 from Advances in Neural Information Processing Systems 36

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RISE: Robust Individualized Decision Learning with Sensitive Variables

Xiaoqing Tan, Zhengling Qi, Christopher Seymour, Lu Tang p19484-19498 from Advances in Neural Information Processing Systems 35

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Risk Bounds of Multi-Pass SGD for Least Squares in the Interpolation Regime

Difan Zou, Jingfeng Wu, Vladimir Braverman, Quanquan Gu, Sham Kakade p12909-12920 from Advances in Neural Information Processing Systems 35

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Risk-Averse Active Sensing for Timely Outcome Prediction under Cost Pressure

Yuchao Qin, Mihaela Van Der Schaar, Changhee Lee p6397-6411 from Advances in Neural Information Processing Systems 36

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Risk-Averse Fine-tuning of Large Language Models

Sapana Chaudhary, Ujwal Dinesha, Dileep Kalathil, Srinivas Shakkottai p107003-107038 from Advances in Neural Information Processing Systems 37

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Risk-Averse Model Uncertainty for Distributionally Robust Safe Reinforcement Learning

James Queeney, Mouhacine Benosman p1659-1680 from Advances in Neural Information Processing Systems 36

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Risk-Driven Design of Perception Systems

Anthony Corso, Sydney Katz, Craig Innes, Xin Du, Subramanian Ramamoorthy, Mykel J Kochenderfer p9894-9906 from Advances in Neural Information Processing Systems 35

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Risk-sensitive control as inference with Rényi divergence

Kaito Ito, Kenji Kashima p71381-71413 from Advances in Neural Information Processing Systems 37

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RiskQ: Risk-sensitive Multi-Agent Reinforcement Learning Value Factorization

Siqi Shen, Chennan Ma, Chao Li, Weiquan Liu, Yongquan Fu, Songzhu Mei, Xinwang Liu, Cheng Wang p34791-34825 from Advances in Neural Information Processing Systems 36

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RKHS-SHAP: Shapley Values for Kernel Methods

Siu Lun Chau, Robert Hu, Javier González, Dino Sejdinovic p13050-13063 from Advances in Neural Information Processing Systems 35

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Neural Information Processing Systems Foundation, Inc. (NeurIPS)

RGMDT: Return-Gap-Minimizing Decision Tree Extraction in Non-Euclidean Metric Space

RGMIL: Guide Your Multiple-Instance Learning Model with Regressor

RH-BrainFS: Regional Heterogeneous Multimodal Brain Networks Fusion Strategy

Richelieu: Self-Evolving LLM-Based Agents for AI Diplomacy

Riemannian Diffusion Models

Riemannian Laplace approximations for Bayesian neural networks

Riemannian Neural SDE: Learning Stochastic Representations on Manifolds

Riemannian Projection-free Online Learning

Riemannian Residual Neural Networks

Riemannian SAM: Sharpness-Aware Minimization on Riemannian Manifolds

Riemannian Score-Based Generative Modelling

Riemannian stochastic optimization methods avoid strict saddle points

Right this way: Can VLMs Guide Us to See More to Answer Questions?

Rigorous Runtime Analysis of MOEA/D for Solving Multi-Objective Minimum Weight Base Problems

RIO: A Benchmark for Reasoning Intention-Oriented Objects in Open Environments

RISE: Robust Individualized Decision Learning with Sensitive Variables

Risk Bounds of Multi-Pass SGD for Least Squares in the Interpolation Regime

Risk-Averse Active Sensing for Timely Outcome Prediction under Cost Pressure

Risk-Averse Fine-tuning of Large Language Models

Risk-Averse Model Uncertainty for Distributionally Robust Safe Reinforcement Learning

Risk-Driven Design of Perception Systems

Risk-sensitive control as inference with Rényi divergence

RiskQ: Risk-sensitive Multi-Agent Reinforcement Learning Value Factorization

RKHS-SHAP: Shapley Values for Kernel Methods

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