The Emerging Trends of Multi-Label Learning

The Emerging Trends of Multi-Label Learning

23 November 2020

Ivor W. Tsang

Papers citing "The Emerging Trends of Multi-Label Learning"

8 / 8 papers shown

Title
Towards Fine-Grained Webpage Fingerprinting at Scale Xiyuan Zhao Xinhao Deng Qi Li Yunpeng Liu Zhuotao Liu Kun Sun Ke Xu 24 2 0 06 Sep 2024
Adaptive Collaborative Correlation Learning-based Semi-Supervised Multi-Label Feature Selection Yanyong Huang Li Yang Dongjie Wang Ke Li Xiuwen Yi Fengmao Lv Tianrui Li 18 0 0 18 Jun 2024
Boosting Single Positive Multi-label Classification with Generalized Robust Loss Yanxi Chen Chunxiao Li Xinyang Dai Jinhuan Li Weiyu Sun Yiming Wang Renyuan Zhang Tinghe Zhang Bo Wang 21 0 0 06 May 2024
CPR-Coach: Recognizing Composite Error Actions based on Single-class Training Shunli Wang Qing Yu Shuai Wang Dingkang Yang Liuzhen Su Xiao Zhao Haopeng Kuang Pei Zhang Peng Zhai Lihua Zhang 21 3 0 21 Sep 2023
SimFair: A Unified Framework for Fairness-Aware Multi-Label Classification Tianci Liu Haoyu Wang Yaqing Wang Xiaoqian Wang Lu Su Jing Gao 14 6 0 19 Feb 2023
Learning Disentangled Label Representations for Multi-label Classification Jian Jia Fei He Naiyu Gao Xiaotang Chen Kaiqi Huang 13 2 0 02 Dec 2022
Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam Mohammad Emtiyaz Khan Didrik Nielsen Voot Tangkaratt Wu Lin Y. Gal Akash Srivastava ODL 71 264 0 13 Jun 2018
Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results Antti Tarvainen Harri Valpola OOD MoMe 244 1,279 0 06 Mar 2017