Papers
Probably Approximate Shapley Fairness with Applications in Machine Learning
Zijian Zhou, Xinyi Xu, Rachael Hwee Ling Sim et al.
Progress and Limitations of Deep Networks to Recognize Objects in Unusual Poses
Amro Abbas, Stéphane Deny
Progressive Bayesian Inference for Scribble-Supervised Semantic Segmentation
Chuanwei Zhou, Chunyan Xu, Zhen Cui
Progressive Deep Multi-View Comprehensive Representation Learning
Cai Xu, Wei Zhao, Jinglong Zhao et al.
Progressive Few-Shot Adaptation of Generative Model with Align-Free Spatial Correlation
Jongbo Moon, Hyunjun Kim, Jae-Pil Heo
Progressive Multi-View Human Mesh Recovery with Self-Supervision
Xuan Gong, Liangchen Song, Meng Zheng et al.
Progressive Neighborhood Aggregation for Semantic Segmentation Refinement
Ting Liu, Yunchao Wei, Yanning Zhang
ProKD: An Unsupervised Prototypical Knowledge Distillation Network for Zero-Resource Cross-Lingual Named Entity Recognition
Ling Ge, Chunming Hu, Guanghui Ma et al.
Prompt-Augmented Linear Probing: Scaling beyond the Limit of Few-Shot In-Context Learners
Hyunsoo Cho, Hyuhng Joon Kim, Junyeob Kim et al.
Prompting Neural Machine Translation with Translation Memories
Abudurexiti Reheman, Tao Zhou, Yingfeng Luo et al.
Properties of Position Matrices and Their Elections
Niclas Boehmer, Jin-Yi Cai, Piotr Faliszewski et al.
Proportional Decisions in Perpetual Voting
Martin Lackner, Jan Maly
Proportionality in Approval-Based Participatory Budgeting
Markus Brill, Stefan Forster, Martin Lackner et al.
Prototypical Fine-Tuning: Towards Robust Performance under Varying Data Sizes
Yiqiao Jin, Xiting Wang, Yaru Hao et al.
Prototypical Partial Optimal Transport for Universal Domain Adaptation
Yucheng Yang, Xiang Gu, Jian Sun
Prototyping Logic-Based AI Services with LogicUS
Víctor Ramos-González, Joaquín Borrego-Díaz, Fernando Sancho-Caparrini
Provable Detection of Propagating Sampling Bias in Prediction Models
Pavan Ravishankar, Qingyu Mo, Edward McFowland III et al.
Provable Pathways: Learning Multiple Tasks over Multiple Paths
Yingcong Li, Samet Oymak
Provably Efficient Causal Model-Based Reinforcement Learning for Systematic Generalization
Mirco Mutti, Riccardo De Santi, Emanuele Rossi et al.
Proximal Stochastic Recursive Momentum Methods for Nonconvex Composite Decentralized Optimization
Gabriel Mancino-Ball, Shengnan Miao, Yangyang Xu et al.
ProxyBO: Accelerating Neural Architecture Search via Bayesian Optimization with Zero-Cost Proxies
Yu Shen, Yang Li, Jian Zheng et al.
Pseudo Label-Guided Model Inversion Attack via Conditional Generative Adversarial Network
Xiaojian Yuan, Kejiang Chen, Jie Zhang et al.
PUnifiedNER: A Prompting-Based Unified NER System for Diverse Datasets
Jinghui Lu, Rui Zhao, Brian Mac Namee et al.
PUPS: Point Cloud Unified Panoptic Segmentation
Shihao Su, Jianyun Xu, Huanyu Wang et al.