ACML 2020
54 papers
A One-Step Approach to Covariate Shift Adaptation
Tianyi Zhang, Ikko Yamane, Nan Lu, Masashi Sugiyama Bidirectional Dependency-Guided Attention for Relation Extraction
Xingchen Deng, Lei Zhang, Yixing Fan, Long Bai, Jiafeng Guo, Pengfei Wang Collaborative Exploration in Stochastic Multi-Player Bandits
Hiba Dakdouk, Raphaël Féraud, Nadège Varsier, Patrick Maillé Constrained Reinforcement Learning via Policy Splitting
Haoxian Chen, Henry Lam, Fengpei Li, Amirhossein Meisami Deep Dynamic Boosted Forest
Haixin Wang, Xingzhang Ren, Jinan Sun, Wei Ye, Long Chen, Muzhi Yu, Shikun Zhang DFQF: Data Free Quantization-Aware Fine-Tuning
Bowen Li, Kai Huang, Siang Chen, Dongliang Xiong, Haitian Jiang, Luc Claesen Efficient Attention Calibration Network for Real-Time Semantic Segmentation
Hengfeng Zha, Rui Liu, Dongsheng Zhou, Xin Yang, Qiang Zhang, Xiaopeng Wei Foolproof Cooperative Learning
Alexis Jacq, Julien Perolat, Matthieu Geist, Olivier Pietquin Learning Interpretable Models Using Soft Integrity Constraints
Khaled Belahcène, Nataliya Sokolovska, Yann Chevaleyre, Jean-Daniel Zucker Proxy Network for Few Shot Learning
Bin Xiao, Chien-Liang Liu, Wen-Hoar Hsaio Randomness Efficient Feature Hashing for Sparse Binary Data
Rameshwar Pratap, Karthik Revanuru, Anirudh Ravi, Raghav Kulkarni Robust Document Distance with Wasserstein-Fisher-Rao Metric
Zihao Wang, Datong Zhou, Ming Yang, Yong Zhang, Chenglong Rao, Hao Wu Scaling up Simhash
Rameshwar Pratap, Anup Deshmukh, Pratheeksha Nair, Anirudh Ravi