18 citations · 139 across the 44 of their papers we have counts for
4 papers · 1 filter
Towards Redundancy-Free Sub-networks in Continual Learning
Cheng Chen, Jingkuan Song, LianLi Gao +1
Catastrophic Forgetting (CF) is a prominent issue in continual learning. Parameter isolation addresses this challenge by masking a sub-network for each task to mitigate interferenc…
A Closer Look at Few-shot Classification Again
Xu Luo, Hao Wu, Ji Zhang +3
Few-shot classification consists of a training phase where a model is learned on a relatively large dataset and an adaptation phase where the learned model is adapted to previously…
Unsupervised Domain-adaptive Hash for Networks
Tao He, Lianli Gao, Jingkuan Song +1
Abundant real-world data can be naturally represented by large-scale networks, which demands efficient and effective learning algorithms. At the same time, labels may only be avail…
Semi-supervised Network Embedding with Differentiable Deep Quantisation
Tao He, Lianli Gao, Jingkuan Song +1
Learning accurate low-dimensional embeddings for a network is a crucial task as it facilitates many downstream network analytics tasks. For large networks, the trained embeddings o…