343 citations · 805 across the 37 of their papers we have counts for
7 papers · 1 filter
CLCLSA: Cross-omics Linked embedding with Contrastive Learning and Self Attention for multi-omics integration with incomplete multi-omics data
Chen Zhao, Anqi Liu, Xiao Zhang +6
Integration of heterogeneous and high-dimensional multi-omics data is becoming increasingly important in understanding genetic data. Each omics technique only provides a limited vi…
Local Learning Matters: Rethinking Data Heterogeneity in Federated Learning
Matias Mendieta, Taojiannan Yang, Pu Wang +3
Federated learning (FL) is a promising strategy for performing privacy-preserving, distributed learning with a network of clients (i.e., edge devices). However, the data distributi…
A Unified Joint Maximum Mean Discrepancy for Domain Adaptation
Wei Wang, Baopu Li, Shuhui Yang +6
Domain adaptation has received a lot of attention in recent years, and many algorithms have been proposed with impressive progress. However, it is still not fully explored concerni…
Rethink Maximum Mean Discrepancy for Domain Adaptation
Wei Wang, Haojie Li, Zhengming Ding +1
Existing domain adaptation methods aim to reduce the distributional difference between the source and target domains and respect their specific discriminative information, by estab…
Importance Filtered Cross-Domain Adaptation
Wei Wang, Haojie Li, Zhihui Wang +3
In Domain Adaptation (DA), the category-relevant losses usually occupy a dominant position, while they are usually built with hard or soft labels in existing models. We observed th…
Learning Robust Data Representation: A Knowledge Flow Perspective
Zhengming Ding, Ming Shao, Handong Zhao +1
It is always demanding to learn robust visual representation for various learning problems; however, this learning and maintenance process usually suffers from noise, incompletenes…
Consensus Clustering: An Embedding Perspective, Extension and Beyond
Hongfu Liu, Zhiqiang Tao, Zhengming Ding
Consensus clustering fuses diverse basic partitions (i.e., clustering results obtained from conventional clustering methods) into an integrated one, which has attracted increasing…