3 citations · 3 across the 5 of their papers we have counts for
4 papers · 1 filter
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…
Towards a Robust Differentiable Architecture Search under Label Noise
Christian Simon, Piotr Koniusz, Lars Petersson +2
Neural Architecture Search (NAS) is the game changer in designing robust neural architectures. Architectures designed by NAS outperform or compete with the best manual network desi…
On Learning the Geodesic Path for Incremental Learning
Christian Simon, Piotr Koniusz, Mehrtash Harandi
Neural networks notoriously suffer from the problem of catastrophic forgetting, the phenomenon of forgetting the past knowledge when acquiring new knowledge. Overcoming catastrophi…
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…