20 citations · 47 across the 11 of their papers we have counts for
4 papers · 1 filter
Memory Efficient Class-Incremental Learning for Image Classification
Hanbin Zhao, Hui Wang, Yongjian Fu +2
With the memory-resource-limited constraints, class-incremental learning (CIL) usually suffers from the "catastrophic forgetting" problem when updating the joint classification mod…
What and Where: Learn to Plug Adapters via NAS for Multi-Domain Learning
Hanbin Zhao, Hao Zeng, Xin Qin +4
As an important and challenging problem, multi-domain learning (MDL) typically seeks for a set of effective lightweight domain-specific adapter modules plugged into a common domain…
MgSvF: Multi-Grained Slow vs. Fast Framework for Few-Shot Class-Incremental Learning
Hanbin Zhao, Yongjian Fu, Mintong Kang +3
As a challenging problem, few-shot class-incremental learning (FSCIL) continually learns a sequence of tasks, confronting the dilemma between slow forgetting of old knowledge and f…
Epoch-evolving Gaussian Process Guided Learning
Jiabao Cui, Xuewei Li, Bin Li +3
In this paper, we propose a novel learning scheme called epoch-evolving Gaussian Process Guided Learning (GPGL), which aims at characterizing the correlation information between th…