26 citations · 29 across the 6 of their papers we have counts for
6 papers
Many-to-Many Matching via Sparsity Controlled Optimal Transport
Weijie Liu, Han Bao, Makoto Yamada +3
Many-to-many matching seeks to match multiple points in one set and multiple points in another set, which is a basis for a wide range of data mining problems. It can be naturally r…
MCA: Moment Channel Attention Networks
Yangbo Jiang, Zhiwei Jiang, Le Han +2
Channel attention mechanisms endeavor to recalibrate channel weights to enhance representation abilities of networks. However, mainstream methods often rely solely on global averag…
Towards Domain-Specific Features Disentanglement for Domain Generalization
Hao Chen, Qi Zhang, Zenan Huang +2
Distributional shift between domains poses great challenges to modern machine learning algorithms. The domain generalization (DG) signifies a popular line targeting this issue, whe…
Latent Processes Identification From Multi-View Time Series
Zenan Huang, Haobo Wang, Junbo Zhao +1
Understanding the dynamics of time series data typically requires identifying the unique latent factors for data generation, \textit{a.k.a.}, latent processes identification. Drive…
Discriminative Radial Domain Adaptation
Zenan Huang, Jun Wen, Siheng Chen +2
Domain adaptation methods reduce domain shift typically by learning domain-invariant features. Most existing methods are built on distribution matching, e.g., adversarial domain ad…
Interventional Domain Adaptation
Jun Wen, Changjian Shui, Kun Kuang +4
Domain adaptation (DA) aims to transfer discriminative features learned from source domain to target domain. Most of DA methods focus on enhancing feature transferability through d…