2 citations · 2 across the 8 of their papers we have counts for
8 papers · 1 filter
Unified Optimization of Source Weights and Transfer Quantities in Multi-Source Transfer Learning: An Asymptotic Framework
Qingyue Zhang, Chang Chu, Haohao Fu +5
In multi-source transfer learning, a key challenge lies in how to appropriately differentiate and utilize heterogeneous source tasks. However, existing multi-source methods typical…
SDG-L: A Semiparametric Deep Gaussian Process based Framework for Battery Capacity Prediction
Hanbing Liu, Yanru Wu, Yang Li +2
Lithium-ion batteries are becoming increasingly omnipresent in energy supply. However, the durability of energy storage using lithium-ion batteries is threatened by their dropping…
Reinforced Domain Selection for Continuous Domain Adaptation
Hanbing Liu, Huaze Tang, Yanru Wu +2
Continuous Domain Adaptation (CDA) effectively bridges significant domain shifts by progressively adapting from the source domain through intermediate domains to the target domain.…
Understanding Knowledge Transferability for Transfer Learning: A Survey
Haohua Wang, Jingge Wang, Zijie Zhao +9
Transfer learning has become an essential paradigm in artificial intelligence, enabling the transfer of knowledge from a source task to improve performance on a target task. This a…
Exploiting Task Relationships in Continual Learning via Transferability-Aware Task Embeddings
Yanru Wu, Jianning Wang, Xiangyu Chen +4
Continual learning (CL) has been a critical topic in contemporary deep neural network applications, where higher levels of both forward and backward transfer are desirable for an e…
A High-Dimensional Statistical Method for Optimizing Transfer Quantities in Multi-Source Transfer Learning
Qingyue Zhang, Haohao Fu, Guanbo Huang +7
Multi-source transfer learning provides an effective solution to data scarcity in real-world supervised learning scenarios by leveraging multiple source tasks. In this field, exist…