Fine-grained generalization analysis of vector-valued learning

• Main Authors: WU, Liang, LEDENT, Antoine, LEI, Yunwen, KLOFT, Marius
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2021
• Subjects: Statistical Learning Theory; Multi-label Learning; Stochastic Gradient Descent; Artificial Intelligence and Robotics; Theory and Algorithms
• Online Access: https://ink.library.smu.edu.sg/sis_research/7203; https://ink.library.smu.edu.sg/context/sis_research/article/8206/viewcontent/vector_val.pdf
• Institution: Singapore Management University

Many fundamental machine learning tasks can be formulated as a problem of learning with vector-valued functions, where we learn multiple scalar-valued functions together. Although there is some generalization analysis on different specific algorithms under the empirical risk minimization principle,...