Papers
Posistive-Unlabeled Learning via Optimal Transport and Margin Distribution
Nan Cao, Teng Zhang, Xuanhua Shi et al.
Positive-Unlabeled Learning with Adversarial Data Augmentation for Knowledge Graph Completion
Zhenwei Tang, Shichao Pei, Zhao Zhang et al.
Possibilistic Logic Underlies Abstract Dialectical Frameworks
Jesse Heyninck, Gabriele Kern-Isberner, Tjitze Rienstra et al.
Post-processing of Differentially Private Data: A Fairness Perspective
Keyu Zhu, Ferdinando Fioretto, Pascal Van Hentenryck
PPT: Backdoor Attacks on Pre-trained Models via Poisoned Prompt Tuning
Wei Du, Yichun Zhao, Boqun Li et al.
Predictive Coding: Towards a Future of Deep Learning beyond Backpropagation?
Beren Millidge, Tommaso Salvatori, Yuhang Song et al.
Preserving Consistency in Multi-Issue Liquid Democracy
Rachael Colley, Umberto Grandi
Private Semi-Supervised Federated Learning
Chenyou Fan, Junjie Hu, Jianwei Huang
Private Stochastic Convex Optimization and Sparse Learning with Heavy-tailed Data Revisited
Youming Tao, Yulian Wu, Xiuzhen Cheng et al.
PRNet: Point-Range Fusion Network for Real-Time LiDAR Semantic Segmentation
Xiaoyan Li, Gang Zhang, Tao Jiang et al.
Prompting to Distill: Boosting Data-Free Knowledge Distillation via Reinforced Prompt
Xinyin Ma, Xinchao Wang, Gongfan Fang et al.
Proportional Budget Allocations: Towards a Systematization
Maaike Los, Zoé Christoff, Davide Grossi
Propose-and-Refine: A Two-Stage Set Prediction Network for Nested Named Entity Recognition
Shuhui Wu, Yongliang Shen, Zeqi Tan et al.
Propositional Gossip Protocols under Fair Schedulers
Joseph Livesey, Dominik Wojtczak
Proximity Enhanced Graph Neural Networks with Channel Contrast
Wei Zhuo, Guang Tan
Pruning-as-Search: Efficient Neural Architecture Search via Channel Pruning and Structural Reparameterization
Yanyu Li, Pu Zhao, Geng Yuan et al.
Pseudo-spherical Knowledge Distillation
Kyungmin Lee, Hyeongkeun Lee
Psychiatric Scale Guided Risky Post Screening for Early Detection of Depression
Zhiling Zhang, Siyuan Chen, Mengyue Wu et al.
Public Signaling in Bayesian Ad Auctions
Francesco Bacchiocchi, Matteo Castiglioni, Alberto Marchesi et al.
QCDCL with Cube Learning or Pure Literal Elimination - What is Best?
Benjamin Böhm, Tomáš Peitl, Olaf Beyersdorff
Quantifying Health Inequalities Induced by Data and AI Models
Honghan Wu, Aneeta Sylolypavan, Minhong Wang et al.
Quaternion Ordinal Embedding
Wenzheng Hou, Qianqian Xu, Ke Ma et al.
Rainy WCity: A Real Rainfall Dataset with Diverse Conditions for Semantic Driving Scene Understanding
Xian Zhong, Shidong Tu, Xianzheng Ma et al.