Metric-Based Semi-Supervised Regression
Regression problems are present in many industrial applications, and many supervised learning algorithms have been devised over decades. However, available labeled examples are limited in some application settings; meanwhile, enormous unlabeled examples are relatively easy to collect. Thus, this wor...
Main Authors: | Chien-Liang Liu, Qing-Hong Chen |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2020-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/8979413/ |
Similar Items
-
Intention-guided deep semi-supervised document clustering via metric learning
by: Li Jingnan, et al.
Published: (2023-01-01) -
Semi-Supervised Deep Metric Learning Networks for Classification of Polarimetric SAR Data
by: Hongying Liu, et al.
Published: (2020-05-01) -
Distributed Semi-Supervised Metric Learning
by: Pengcheng Shen, et al.
Published: (2016-01-01) -
High-Rankness Regularized Semi-Supervised Deep Metric Learning for Remote Sensing Imagery
by: Jian Kang, et al.
Published: (2020-08-01) -
Efficient Information-Theoretic Large-Scale Semi-Supervised Metric Learning via Proxies
by: Peng Chen, et al.
Published: (2023-08-01)