Papers
PAC-Net: A Model Pruning Approach to Inductive Transfer Learning
Sanghoon Myung, In Huh, Wonik Jang et al.
PAGE-PG: A Simple and Loopless Variance-Reduced Policy Gradient Method with Probabilistic Gradient Estimation
Matilde Gargiani, Andrea Zanelli, Andrea Martinelli et al.
Pairwise Conditional Gradients without Swap Steps and Sparser Kernel Herding
Kazuma K Tsuji, Ken’Ichiro Tanaka, Sebastian Pokutta
Parametric Visual Program Induction with Function Modularization
Xuguang Duan, Xin Wang, Ziwei Zhang et al.
Parsimonious Learning-Augmented Caching
Sungjin Im, Ravi Kumar, Aditya Petety et al.
Partial and Asymmetric Contrastive Learning for Out-of-Distribution Detection in Long-Tailed Recognition
Haotao Wang, Aston Zhang, Yi Zhu et al.
Partial Counterfactual Identification from Observational and Experimental Data
Junzhe Zhang, Jin Tian, Elias Bareinboim
Partial disentanglement for domain adaptation
Lingjing Kong, Shaoan Xie, Weiran Yao et al.
Partial Label Learning via Label Influence Function
Xiuwen Gong, Dong Yuan, Wei Bao
Particle Transformer for Jet Tagging
Huilin Qu, Congqiao Li, Sitian Qian
Path-Aware and Structure-Preserving Generation of Synthetically Accessible Molecules
Juhwan Noh, Dae-Woong Jeong, Kiyoung Kim et al.
pathGCN: Learning General Graph Spatial Operators from Paths
Moshe Eliasof, Eldad Haber, Eran Treister
Path-Gradient Estimators for Continuous Normalizing Flows
Lorenz Vaitl, Kim Andrea Nicoli, Shinichi Nakajima et al.
PDE-Based Optimal Strategy for Unconstrained Online Learning
Zhiyu Zhang, Ashok Cutkosky, Ioannis Paschalidis
PDO-s3DCNNs: Partial Differential Operator Based Steerable 3D CNNs
Zhengyang Shen, Tao Hong, Qi She et al.
Penalizing Gradient Norm for Efficiently Improving Generalization in Deep Learning
Yang Zhao, Hao Zhang, Xiuyuan Hu
Perfectly Balanced: Improving Transfer and Robustness of Supervised Contrastive Learning
Mayee Chen, Daniel Y Fu, Avanika Narayan et al.
Permutation Search of Tensor Network Structures via Local Sampling
Chao Li, Junhua Zeng, Zerui Tao et al.
Personalization Improves Privacy-Accuracy Tradeoffs in Federated Learning
Alberto Bietti, Chen-Yu Wei, Miroslav Dudik et al.
Personalized Federated Learning through Local Memorization
Othmane Marfoq, Giovanni Neglia, Richard Vidal et al.
Personalized Federated Learning via Variational Bayesian Inference
Xu Zhang, Yinchuan Li, Wenpeng Li et al.
Pessimism meets VCG: Learning Dynamic Mechanism Design via Offline Reinforcement Learning
Boxiang Lyu, Zhaoran Wang, Mladen Kolar et al.
Pessimistic Minimax Value Iteration: Provably Efficient Equilibrium Learning from Offline Datasets
Han Zhong, Wei Xiong, Jiyuan Tan et al.
Pessimistic Q-Learning for Offline Reinforcement Learning: Towards Optimal Sample Complexity
Laixi Shi, Gen Li, Yuting Wei et al.
Phasic Self-Imitative Reduction for Sparse-Reward Goal-Conditioned Reinforcement Learning
Yunfei Li, Tian Gao, Jiaqi Yang et al.