most citedOnline Deep Learning based on Auto-Encoder

10 citations · 23 across the 7 of their papers we have counts for

collaborators

7 papers

cs.LG20222 cited

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…

cs.LG2022

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…

cs.LG202210 cited

Online Deep Learning based on Auto-Encoder

Si-si Zhang, Jian-wei Liu, Xin Zuo +2

Online learning is an important technical means for sketching massive real-time and high-speed data. Although this direction has attracted intensive attention, most of the literatu…

cs.CV20227 cited

Multi-View representation learning in Multi-Task Scene

Run-kun Lu, Jian-wei Liu, Si-ming Lian +1

Over recent decades have witnessed considerable progress in whether multi-task learning or multi-view learning, but the situation that consider both learning scenes simultaneously…

cs.LG2022

Multi-granularity Relabeled Under-sampling Algorithm for Imbalanced Data

Qi Dai, Jian-wei Liu, Yang Liu

The imbalanced classification problem turns out to be one of the important and challenging problems in data mining and machine learning. The performances of traditional classifiers…

cs.LG20224 cited

Auto-Encoder based Co-Training Multi-View Representation Learning

Run-kun Lu, Jian-wei Liu, Yuan-fang Wang +2

Multi-view learning is a learning problem that utilizes the various representations of an object to mine valuable knowledge and improve the performance of learning algorithm, and o…