33 citations · 125 across the 19 of their papers we have counts for
4 papers · 1 filter
Interpretable Anomaly Detection with Mondrian P{ó}lya Forests on Data Streams
Charlie Dickens, Eric Meissner, Pablo G. Moreno +1
Anomaly detection at scale is an extremely challenging problem of great practicality. When data is large and high-dimensional, it can be difficult to detect which observations do n…
Optimal Continual Learning has Perfect Memory and is NP-hard
Jeremias Knoblauch, Hisham Husain, Tom Diethe
Continual Learning (CL) algorithms incrementally learn a predictor or representation across multiple sequentially observed tasks. Designing CL algorithms that perform reliably and…
Semi-Discriminative Representation Loss for Online Continual Learning
Yu Chen, Tom Diethe, Peter Flach
The use of episodic memory in continual learning has demonstrated effectiveness for alleviating catastrophic forgetting. In recent studies, gradient-based approaches have been deve…
Similarity of Neural Networks with Gradients
Shuai Tang, Wesley J. Maddox, Charlie Dickens +2
A suitable similarity index for comparing learnt neural networks plays an important role in understanding the behaviour of the highly-nonlinear functions, and can provide insights…