21 citations · 75 across the 22 of their papers we have counts for
6 papers · 1 filter
Self-paced Weight Consolidation for Continual Learning
Wei Cong, Yang Cong, Gan Sun +2
Continual learning algorithms which keep the parameters of new tasks close to that of previous tasks, are popular in preventing catastrophic forgetting in sequential task learning…
Federated Class-Incremental Learning
Jiahua Dong, Lixu Wang, Zhen Fang +4
Federated learning (FL) has attracted growing attention via data-private collaborative training on decentralized clients. However, most existing methods unrealistically assume obje…
Lifelong Spectral Clustering
Gan Sun, Yang Cong, Qianqian Wang +2
In the past decades, spectral clustering (SC) has become one of the most effective clustering algorithms. However, most previous studies focus on spectral clustering tasks with a f…
Visual Tactile Fusion Object Clustering
Tao Zhang, Yang Cong, Gan Sun +2
Object clustering, aiming at grouping similar objects into one cluster with an unsupervised strategy, has been extensivelystudied among various data-driven applications. However, m…
Representative Task Self-selection for Flexible Clustered Lifelong Learning
Gan Sun, Yang Cong, Qianqian Wang +2
Consider the lifelong machine learning paradigm whose objective is to learn a sequence of tasks depending on previous experiences, e.g., knowledge library or deep network weights.…
Lifelong Metric Learning
Gan Sun, Yang Cong, Ji Liu +1
The state-of-the-art online learning approaches are only capable of learning the metric for predefined tasks. In this paper, we consider lifelong learning problem to mimic "human l…