Weakly Supervised Representation Learning

Guest Editors: Bo Han, Tongliang Liu, Quanming Yao, Mingming Gong, Gang Niu, Ivor W. Tsang, Masashi Sugiyama

Journal

Machine Learning

Machine Learning is an international forum focusing on computational approaches to learning.

Bo Han

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Tongliang Liu

-
Quanming Yao

-
Mingming Gong

-
Gang Niu

-
Ivor W. Tsang

-
Masashi Sugiyama

-

Showing 1-13 of 13 articles

Autoencoding slow representations for semi-supervised data-efficient regression
Oliver Struckmeier
Kshitij Tiwari
Ville Kyrki
OriginalPaper Open access 25 January 2023 Pages: 2297 - 2315
Model-free inverse reinforcement learning with multi-intention, unlabeled, and overlapping demonstrations
Ariyan Bighashdel
Pavol Jancura
Gijs Dubbelman
OriginalPaper Open access 30 November 2022 Pages: 2263 - 2296
DAFS: a domain aware few shot generative model for event detection
Nan Xia
Hang Yu
Xiangfeng Luo
OriginalPaper 04 September 2022 Pages: 1011 - 1031
Information bottleneck and selective noise supervision for zero-shot learning
Lei Zhou
Yang Liu
Edwin Hancock
OriginalPaper 01 September 2022 Pages: 2239 - 2261
Machine truth serum: a surprisingly popular approach to improving ensemble methods
Tianyi Luo
Yang Liu
OriginalPaper 12 July 2022 Pages: 789 - 815
Beyond confusion matrix: learning from multiple annotators with awareness of instance features
Jingzheng Li
Hailong Sun
Jiyi Li
OriginalPaper 07 July 2022 Pages: 1053 - 1075
An instance-dependent simulation framework for learning with label noise
Keren Gu
Xander Masotto
Dong Yin
OriginalPaper 27 June 2022 Pages: 1871 - 1896
Shift of pairwise similarities for data clustering
Morteza Haghir Chehreghani
OriginalPaper Open access 22 June 2022 Pages: 2025 - 2051
A viable framework for semi-supervised learning on realistic dataset
Hao Chang
Guochen Xie
Ye Yu
OriginalPaper 21 June 2022 Pages: 1847 - 1869
Learning from crowds with sparse and imbalanced annotations
Ye Shi
Shao-Yuan Li
Sheng-Jun Huang
OriginalPaper 14 June 2022 Pages: 1823 - 1845
Learning from self-discrepancy via multiple co-teaching for cross-domain person re-identification
Suncheng Xiang
Yuzhuo Fu
Ting Liu
OriginalPaper 14 June 2022 Pages: 1923 - 1940
Distilling ensemble of explanations for weakly-supervised pre-training of image segmentation models
Xuhong Li
Haoyi Xiong
Dejing Dou
OriginalPaper 09 June 2022 Pages: 2193 - 2209
Troubleshooting image segmentation models with human-in-the-loop
Haotao Wang
Tianlong Chen
Kede Ma
OriginalPaper 27 January 2022 Pages: 1033 - 1051

Weakly Supervised Representation Learning

Participating journal

Machine Learning

Editors

Bo Han

Tongliang Liu

Quanming Yao

Mingming Gong

Gang Niu

Ivor W. Tsang

Masashi Sugiyama

Articles

Autoencoding slow representations for semi-supervised data-efficient regression

Model-free inverse reinforcement learning with multi-intention, unlabeled, and overlapping demonstrations

DAFS: a domain aware few shot generative model for event detection

Information bottleneck and selective noise supervision for zero-shot learning

Machine truth serum: a surprisingly popular approach to improving ensemble methods

Beyond confusion matrix: learning from multiple annotators with awareness of instance features

An instance-dependent simulation framework for learning with label noise

Shift of pairwise similarities for data clustering

A viable framework for semi-supervised learning on realistic dataset

Learning from crowds with sparse and imbalanced annotations

Learning from self-discrepancy via multiple co-teaching for cross-domain person re-identification

Distilling ensemble of explanations for weakly-supervised pre-training of image segmentation models

Troubleshooting image segmentation models with human-in-the-loop

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Weakly Supervised Representation Learning

Participating journal

Editors

Bo Han

Tongliang Liu

Quanming Yao

Mingming Gong

Gang Niu

Ivor W. Tsang

Masashi Sugiyama

Articles

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