2 citations · 3 across the 5 of their papers we have counts for
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GMM Discriminant Analysis with Noisy Label for Each Class
Jian-wei Liu, Zheng-ping Ren, Run-kun Lu +1
Real world datasets often contain noisy labels, and learning from such datasets using standard classification approaches may not produce the desired performance. In this paper, we…
Bilevel Online Deep Learning in Non-stationary Environment
Ya-nan Han, Jian-wei Liu, Bing-biao Xiao +2
Recent years have witnessed enormous progress of online learning. However, a major challenge on the road to artificial agents is concept drift, that is, the data probability distri…
Multi-View Non-negative Matrix Factorization Discriminant Learning via Cross Entropy Loss
Jian-wei Liu, Yuan-fang Wang, Run-kun Lu +1
Multi-view learning accomplishes the task objectives of classification by leverag-ing the relationships between different views of the same object. Most existing methods usually fo…
Multi-view Subspace Adaptive Learning via Autoencoder and Attention
Jian-wei Liu, Hao-jie Xie, Run-kun Lu +1
Multi-view learning can cover all features of data samples more comprehensively, so multi-view learning has attracted widespread attention. Traditional subspace clustering methods,…
Self-attention Multi-view Representation Learning with Diversity-promoting Complementarity
Jian-wei Liu, Xi-hao Ding, Run-kun Lu +1
Multi-view learning attempts to generate a model with a better performance by exploiting the consensus and/or complementarity among multi-view data. However, in terms of complement…