542 citations · 744 across the 16 of their papers we have counts for
4 papers · 1 filter
Prototype Completion with Primitive Knowledge for Few-Shot Learning
Baoquan Zhang, Xutao Li, Yunming Ye +2
Few-shot learning is a challenging task, which aims to learn a classifier for novel classes with few examples. Pre-training based meta-learning methods effectively tackle the probl…
Multi-source Heterogeneous Domain Adaptation with Conditional Weighting Adversarial Network
Yuan Yao, Xutao Li, Yu Zhang +1
Heterogeneous domain adaptation (HDA) tackles the learning of cross-domain samples with both different probability distributions and feature representations. Most of the existing H…
MetaConcept: Learn to Abstract via Concept Graph for Weakly-Supervised Few-Shot Learning
Baoquan Zhang, Ka-Cheong Leung, Yunming Ye +1
Meta-learning has been proved to be an effective framework to address few-shot learning problems. The key challenge is how to minimize the generalization error of base learner acro…
Inter-sequence Enhanced Framework for Personalized Sequential Recommendation
Feng Liu, Weiwen Liu, Xutao Li +1
Modeling the sequential correlation of users' historical interactions is essential in sequential recommendation. However, the majority of the approaches mainly focus on modeling th…