9 citations · 20 across the 5 of their papers we have counts for
5 papers
Exploring Leximin Principle for Fair Core-Selecting Combinatorial Auctions: Payment Rule Design and Implementation
Hao Cheng, Shufeng Kong, Yanchen Deng +4
Core-selecting combinatorial auctions (CAs) restrict the auction result in the core such that no coalitions could improve their utilities by engaging in collusion. The minimum-reve…
Semi-Supervised Learning with Multi-Head Co-Training
Mingcai Chen, Yuntao Du, Yi Zhang +2
Co-training, extended from self-training, is one of the frameworks for semi-supervised learning. Without natural split of features, single-view co-training works at the cost of tra…
Dual Adversarial Domain Adaptation
Yuntao Du, Zhiwen Tan, Qian Chen +3
Unsupervised domain adaptation aims at transferring knowledge from the labeled source domain to the unlabeled target domain. Previous adversarial domain adaptation methods mostly a…
Homogeneous Online Transfer Learning with Online Distribution Discrepancy Minimization
Yuntao Du, Zhiwen Tan, Qian Chen +2
Transfer learning has been demonstrated to be successful and essential in diverse applications, which transfers knowledge from related but different source domains to the target do…
Many could be better than all: A novel instance-oriented algorithm for Multi-modal Multi-label problem
Yi Zhang, Cheng Zeng, Hao Cheng +2
With the emergence of diverse data collection techniques, objects in real applications can be represented as multi-modal features. What's more, objects may have multiple semantic m…