282 citations · 327 across the 11 of their papers we have counts for
12 papers
Outlier detection of vital sign trajectories from COVID-19 patients
Sara Summerton, Ann Tivey, Rohan Shotton +5
In this work, we present a novel trajectory comparison algorithm to identify abnormal vital sign trends, with the aim of improving recognition of deteriorating health. There is gro…
Bias-Variance Decompositions for Margin Losses
Danny Wood, Tingting Mu, Gavin Brown
We introduce a novel bias-variance decomposition for a range of strictly convex margin losses, including the logistic loss (minimized by the classic LogitBoost algorithm), as well…
To Ensemble or Not Ensemble: When does End-To-End Training Fail?
Andrew M. Webb, Charles Reynolds, Wenlin Chen +4
End-to-End training (E2E) is becoming more and more popular to train complex Deep Network architectures. An interesting question is whether this trend will continue-are there any c…
Is feature selection secure against training data poisoning?
Huang Xiao, Battista Biggio, Gavin Brown +3
Learning in adversarial settings is becoming an important task for application domains where attackers may inject malicious data into the training set to subvert normal operation o…
The K-Nearest Neighbour UCB algorithm for multi-armed bandits with covariates
Henry WJ Reeve, Joe Mellor, Gavin Brown
In this paper we propose and explore the k-Nearest Neighbour UCB algorithm for multi-armed bandits with covariates. We focus on a setting where the covariates are supported on a me…
Diversity and degrees of freedom in regression ensembles
Henry WJ Reeve, Gavin Brown
Ensemble methods are a cornerstone of modern machine learning. The performance of an ensemble depends crucially upon the level of diversity between its constituent learners. This p…