794 citations · 2.7k across the 93 of their papers we have counts for
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Bayesian Meta-Learning for the Few-Shot Setting via Deep Kernels
Massimiliano Patacchiola, Jack Turner, Elliot J. Crowley +2
Recently, different machine learning methods have been introduced to tackle the challenging few-shot learning scenario that is, learning from a small labeled dataset related to a s…
BlockSwap: Fisher-guided Block Substitution for Network Compression on a Budget
Jack Turner, Elliot J. Crowley, Michael O'Boyle +2
The desire to map neural networks to varying-capacity devices has led to the development of a wealth of compression techniques, many of which involve replacing standard convolution…
Learning to learn via Self-Critique
Antreas Antoniou, Amos Storkey
In few-shot learning, a machine learning system learns from a small set of labelled examples relating to a specific task, such that it can generalize to new examples of the same ta…
Zero-shot Knowledge Transfer via Adversarial Belief Matching
Paul Micaelli, Amos Storkey
Performing knowledge transfer from a large teacher network to a smaller student is a popular task in modern deep learning applications. However, due to growing dataset sizes and st…