Tensor dictionary-based heterogeneous transfer learning to study emotion-related gender differences in brain

• Published in: Neural networks Vol. 183; p. 106974
• Main Authors: Yang, Lan, Qiao, Chen, Kanamori, Takafumi, Calhoun, Vince D., Stephen, Julia M., Wilson, Tony W., Wang, Yu-Ping
• Format: Journal Article
• Language: English
• Published: United States Elsevier Ltd 01.03.2025
• Subjects: Adolescent; Brain - diagnostic imaging; Brain - physiology; Electroencephalography; Emotion processing; Emotions - physiology; Female; Gender differences; Humans; Machine Learning; Magnetic Resonance Imaging - methods; Male; Sex Characteristics; Tensor dictionary learning; Transfer learning; Transfer, Psychology - physiology; Tensor dictionary learning; Gender differences; Transfer learning; Emotion processing

In practice, collecting auxiliary labeled data with same feature space from multiple domains is difficult. Thus, we focus on the heterogeneous transfer learning to address the problem of insufficient sample sizes in neuroimaging. Viewing subjects, time, and features as dimensions, brain activation a...