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

Gina Adam, Nathaniel Bastian, Jingdi Chen, Carlee Joe-Wong, Tian Lan, Yongsheng Mei, Hanhan Zhou 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, Shuiping Gou, Licheng Jiao, Shasha Mao, Lin Xiong, Yimeng Zhang p35606-35618 from Advances in Neural Information Processing Systems 36

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RH-BrainFS: Regional Heterogeneous Multimodal Brain Networks Fusion Strategy

Youyong Kong, Yueying Li, Hongting Ye, Yonggui Yuan, Ke Zhang, Yalu Zheng 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, Yizhou Wang, Fangwei Zhong p123471-123497 from Advances in Neural Information Processing Systems 37

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Riemannian Diffusion Models

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

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Riemannian Laplace approximations for Bayesian neural networks

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

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Riemannian Neural SDE: Learning Stochastic Representations on Manifolds

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

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Riemannian Projection-free Online Learning

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

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Riemannian Residual Neural Networks

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

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Riemannian SAM: Sharpness-Aware Minimization on Riemannian Manifolds

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

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Riemannian Score-Based Generative Modelling

Valentin De Bortoli, Arnaud Doucet, Michael Hutchinson, Emile Mathieu, Yee Whye Teh, James Thornton 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?

Lei Ding, Leilani Gilpin, Li Liu, Kalyana Tholeti, Diji Yang, Yi Zhang, Sijia Zhong 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

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

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RISE: Robust Individualized Decision Learning with Sensitive Variables

Zhengling Qi, Christopher Seymour, Xiaoqing Tan, 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

Vladimir Braverman, Quanquan Gu, Sham Kakade, Jingfeng Wu, Difan Zou 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

Changhee Lee, Yuchao Qin, Mihaela Van Der Schaar 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

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

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Risk-Driven Design of Perception Systems

Anthony Corso, Xin Du, Craig Innes, Sydney Katz, Mykel J Kochenderfer, Subramanian Ramamoorthy 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

Yongquan Fu, Chao Li, Weiquan Liu, Xinwang Liu, Chennan Ma, Songzhu Mei, Siqi Shen, 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, Javier González, Robert Hu, 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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