Papers
Propagate and Inject: Revisiting Propagation-Based Feature Imputation for Graphs with Partially Observed Features
Daeho Um, Sunoh Kim, Jiwoong Park et al.
Propagation of Chaos for Mean-Field Langevin Dynamics and its Application to Model Ensemble
Atsushi Nitanda, Anzelle Lee, Damian Tan Xing Kai et al.
Proposer-Agent-Evaluator (PAE): Autonomous Skill Discovery For Foundation Model Internet Agents
Yifei Zhou, Qianlan Yang, Kaixiang Lin et al.
ProSec: Fortifying Code LLMs with Proactive Security Alignment
Xiangzhe Xu, Zian Su, Jinyao Guo et al.
Protein Structure Tokenization: Benchmarking and New Recipe
Xinyu Yuan, Zichen Wang, Marcus D. Collins et al.
PROTOCOL: Partial Optimal Transport-enhanced Contrastive Learning for Imbalanced Multi-view Clustering
Xuqian Xue, Yiming Lei, Qi Cai et al.
Proto Successor Measure: Representing the Behavior Space of an RL Agent
Siddhant Agarwal, Harshit Sikchi, Peter Stone et al.
Protriever: End-to-End Differentiable Protein Homology Search for Fitness Prediction
Ruben Weitzman, Peter Mørch Groth, Lood Van Niekerk et al.
Provable and Practical Online Learning Rate Adaptation with Hypergradient Descent
Ya-Chi Chu, Wenzhi Gao, Yinyu Ye et al.
Provable Benefit of Random Permutations over Uniform Sampling in Stochastic Coordinate Descent
Donghwa Kim, Jaewook Lee, Chulhee Yun
Provable Benefits of Unsupervised Pre-training and Transfer Learning via Single-Index Models
Taj Jones-Mccormick, Aukosh Jagannath, Subhabrata Sen
Provable In-Context Vector Arithmetic via Retrieving Task Concepts
Dake Bu, Wei Huang, Andi Han et al.
Provable Length Generalization in Sequence Prediction via Spectral Filtering
Annie Marsden, Evan Dogariu, Naman Agarwal et al.
Provable Maximum Entropy Manifold Exploration via Diffusion Models
Riccardo De Santi, Marin Vlastelica, Ya-Ping Hsieh et al.
Provable Policy Gradient for Robust Average-Reward MDPs Beyond Rectangularity
Qiuhao Wang, Yuqi Zha, Chin Pang Ho et al.
Provable Zero-Shot Generalization in Offline Reinforcement Learning
Zhiyong Wang, Chen Yang, John C.S. Lui et al.
Provably Cost-Sensitive Adversarial Defense via Randomized Smoothing
Yuan Xin, Dingfan Chen, Michael Backes et al.
Provably Efficient Algorithm for Best Scoring Rule Identification in Online Principal-Agent Information Acquisition
Zichen Wang, Chuanhao Li, Huazheng Wang
Provably Efficient Exploration in Inverse Constrained Reinforcement Learning
Bo Yue, Jian Li, Guiliang Liu
Provably Efficient RL for Linear MDPs under Instantaneous Safety Constraints in Non-Convex Feature Spaces
Amirhossein Roknilamouki, Arnob Ghosh, Ming Shi et al.
Provably Improving Generalization of Few-shot models with Synthetic Data
Lan-Cuong Nguyen, Quan Nguyen-Tri, Bang Tran Khanh et al.
Provably Near-Optimal Federated Ensemble Distillation with Negligible Overhead
Won-Jun Jang, Hyeon-Seo Park, Si-Hyeon Lee
PROXSPARSE: REGULARIZED LEARNING OF SEMI-STRUCTURED SPARSITY MASKS FOR PRETRAINED LLMS
Hongyi Liu, Rajarshi Saha, Zhen Jia et al.
Proxy-FDA: Proxy-based Feature Distribution Alignment for Fine-tuning Vision Foundation Models without Forgetting
Chen Huang, Skyler Seto, Hadi Pouransari et al.