3 citations · 3 across the 5 of their papers we have counts for
3 papers · 1 filter
Subspace Distillation for Continual Learning
Kaushik Roy, Christian Simon, Peyman Moghadam +1
An ultimate objective in continual learning is to preserve knowledge learned in preceding tasks while learning new tasks. To mitigate forgetting prior knowledge, we propose a novel…
Meta-Learning for Multi-Label Few-Shot Classification
Christian Simon, Piotr Koniusz, Mehrtash Harandi
Even with the luxury of having abundant data, multi-label classification is widely known to be a challenging task to address. This work targets the problem of multi-label meta-lear…
Reinforced Attention for Few-Shot Learning and Beyond
Jie Hong, Pengfei Fang, Weihao Li +4
Few-shot learning aims to correctly recognize query samples from unseen classes given a limited number of support samples, often by relying on global embeddings of images. In this…