activity
20182022
most citedMulti-Label Learning with Deep Forest

32 citations · 43 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV20221 cited

Class-Level Confidence Based 3D Semi-Supervised Learning

Zhimin Chen, Longlong Jing, Liang Yang +2

Recent state-of-the-art method FlexMatch firstly demonstrated that correctly estimating learning status is crucial for semi-supervised learning (SSL). However, the estimation metho…

cs.SI202010 cited

Judging a Book by Its Cover: The Effect of Facial Perception on Centrality in Social Networks

Dongyu Zhang, Teng Guo, Hanxiao Pan +5

Facial appearance matters in social networks. Individuals frequently make trait judgments from facial clues. Although these face-based impressions lack the evidence to determine va…

cs.LG201932 cited

Multi-Label Learning with Deep Forest

Liang Yang, Xi-Zhu Wu, Yuan Jiang +1

In multi-label learning, each instance is associated with multiple labels and the crucial task is how to leverage label correlations in building models. Deep neural network methods…

cs.LG2019

Forest Representation Learning Guided by Margin Distribution

Shen-Huan Lv, Liang Yang, Zhi-Hua Zhou

In this paper, we reformulate the forest representation learning approach as an additive model which boosts the augmented feature instead of the prediction. We substantially improv…

cs.CV2018

Ego-Downward and Ambient Video based Person Location Association

Liang Yang, Hao Jiang, Jizhong Xiao +1

Using an ego-centric camera to do localization and tracking is highly needed for urban navigation and indoor assistive system when GPS is not available or not accurate enough. The…