Papers
8,340 papers found
Probabilistic Imputation for Time-series Classification with Missing Data
Seunghyun Kim, Hyunsu Kim, Eunggu Yun et al.
Probabilistic Unrolling: Scalable, Inverse-Free Maximum Likelihood Estimation for Latent Gaussian Models
Alexander Lin, Bahareh Tolooshams, Yves Atchade et al.
Probably Anytime-Safe Stochastic Combinatorial Semi-Bandits
Yunlong Hou, Vincent Y. F. Tan, Zixin Zhong
Progressive Purification for Instance-Dependent Partial Label Learning
Ning Xu, Biao Liu, Jiaqi Lv et al.
Projected Tensor Power Method for Hypergraph Community Recovery
Jinxin Wang, Yuen-Man Pun, Xiaolu Wang et al.
Prometheus: Taming Sample and Communication Complexities in Constrained Decentralized Stochastic Bilevel Learning
Zhuqing Liu, Xin Zhang, Prashant Khanduri et al.
PromptBoosting: Black-Box Text Classification with Ten Forward Passes
Bairu Hou, Joe O’Connor, Jacob Andreas et al.
Prompting Large Language Model for Machine Translation: A Case Study
Biao Zhang, Barry Haddow, Alexandra Birch
Propensity Matters: Measuring and Enhancing Balancing for Recommendation
Haoxuan Li, Yanghao Xiao, Chunyuan Zheng et al.
Proper Losses for Discrete Generative Models
Dhamma Kimpara, Rafael Frongillo, Bo Waggoner
Proper Scoring Rules for Survival Analysis
Hiroki Yanagisawa
Properties of the Mallows Model Depending on the Number of Alternatives: A Warning for an Experimentalist
Niclas Boehmer, Piotr Faliszewski, Sonja Kraiczy
Protecting Language Generation Models via Invisible Watermarking
Xuandong Zhao, Yu-Xiang Wang, Lei Li
Prototype-oriented unsupervised anomaly detection for multivariate time series
Yuxin Li, Wenchao Chen, Bo Chen et al.
Prototype-Sample Relation Distillation: Towards Replay-Free Continual Learning
Nader Asadi, Mohammadreza Davari, Sudhir Mudur et al.
ProtST: Multi-Modality Learning of Protein Sequences and Biomedical Texts
Minghao Xu, Xinyu Yuan, Santiago Miret et al.
Provable Benefit of Mixup for Finding Optimal Decision Boundaries
Junsoo Oh, Chulhee Yun
Provable Data Subset Selection For Efficient Neural Networks Training
Murad Tukan, Samson Zhou, Alaa Maalouf et al.
Provable Dynamic Fusion for Low-Quality Multimodal Data
Qingyang Zhang, Haitao Wu, Changqing Zhang et al.
Provable Multi-instance Deep AUC Maximization with Stochastic Pooling
Dixian Zhu, Bokun Wang, Zhi Chen et al.
Provable Reset-free Reinforcement Learning by No-Regret Reduction
Hoai-An Nguyen, Ching-An Cheng
Provably Convergent Schrödinger Bridge with Applications to Probabilistic Time Series Imputation
Yu Chen, Wei Deng, Shikai Fang et al.
Provably Efficient Offline Reinforcement Learning with Perturbed Data Sources
Chengshuai Shi, Wei Xiong, Cong Shen et al.
Provably Efficient Representation Learning with Tractable Planning in Low-Rank POMDP
Jiacheng Guo, Zihao Li, Huazheng Wang et al.