21 citations · 72 across the 13 of their papers we have counts for
4 papers · 1 filter
Prototype Fission: Closing Set for Robust Open-set Semi-supervised Learning
Xuwei Tan, Yi-Jie Huang, Yaqian Li
Semi-supervised Learning (SSL) has been proven vulnerable to out-of-distribution (OOD) samples in realistic large-scale unsupervised datasets due to over-confident pseudo-labeling…
Simple and Robust Loss Design for Multi-Label Learning with Missing Labels
Youcai Zhang, Yuhao Cheng, Xinyu Huang +4
Multi-label learning in the presence of missing labels (MLML) is a challenging problem. Existing methods mainly focus on the design of network structures or training schemes, which…
Towards Communication-Efficient and Privacy-Preserving Federated Representation Learning
Haizhou Shi, Youcai Zhang, Zijin Shen +4
This paper investigates the feasibility of federated representation learning under the constraints of communication cost and privacy protection. Existing works either conduct annot…
On the Efficacy of Small Self-Supervised Contrastive Models without Distillation Signals
Haizhou Shi, Youcai Zhang, Siliang Tang +4
It is a consensus that small models perform quite poorly under the paradigm of self-supervised contrastive learning. Existing methods usually adopt a large off-the-shelf model to t…