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cs.LG2018

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…

cs.LG2018

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…

cs.LG2018

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…

cs.LG2018

Minimax rates for cost-sensitive learning on manifolds with approximate nearest neighbours

Henry WJ Reeve, Gavin Brown

We study the approximate nearest neighbour method for cost-sensitive classification on low-dimensional manifolds embedded within a high-dimensional feature space. We determine the…

cs.LG2017

Is Deep Learning Safe for Robot Vision? Adversarial Examples against the iCub Humanoid

Marco Melis, Ambra Demontis, Battista Biggio +3

Deep neural networks have been widely adopted in recent years, exhibiting impressive performances in several application domains. It has however been shown that they can be fooled…