154 citations · 581 across the 79 of their papers we have counts for
11 papers · 2 filters
Taming Overconfident Prediction on Unlabeled Data from Hindsight
Jing Li, Yuangang Pan, Ivor W. Tsang
Minimizing prediction uncertainty on unlabeled data is a key factor to achieve good performance in semi-supervised learning (SSL). The prediction uncertainty is typically expressed…
TRIP: Refining Image-to-Image Translation via Rival Preferences
Yinghua Yao, Yuangang Pan, Ivor W. Tsang +1
Relative attribute (RA), referring to the preference over two images on the strength of a specific attribute, can enable fine-grained image-to-image translation due to its rich sem…
Reasonable Effectiveness of Random Weighting: A Litmus Test for Multi-Task Learning
Baijiong Lin, Feiyang Ye, Yu Zhang +1
Multi-Task Learning (MTL) has achieved success in various fields. However, how to balance different tasks to achieve good performance is a key problem. To achieve the task balancin…
Deep Safe Multi-Task Learning
Zhixiong Yue, Feiyang Ye, Yu Zhang +2
In recent years, Multi-Task Learning (MTL) has attracted much attention due to its good performance in many applications. However, many existing MTL models cannot guarantee that th…
Edge but not Least: Cross-View Graph Pooling
Xiaowei Zhou, Jie Yin, Ivor W. Tsang
Graph neural networks have emerged as a powerful model for graph representation learning to undertake graph-level prediction tasks. Various graph pooling methods have been develope…
A Multi-view Multi-task Learning Framework for Multi-variate Time Series Forecasting
Jinliang Deng, Xiusi Chen, Renhe Jiang +2
Multi-variate time series (MTS) data is a ubiquitous class of data abstraction in the real world. Any instance of MTS is generated from a hybrid dynamical system and their specific…