137 citations · 488 across the 26 of their papers we have counts for
Showing 2018Show all
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cs.AI2018★ 3 cited
LEAFAGE: Example-based and Feature importance-based Explanationsfor Black-box ML models
Ajaya Adhikari, D. M. J Tax, Riccardo Satta +1
As machine learning models become more accurate, they typically become more complex and uninterpretable by humans. The black-box character of these models holds back its acceptance…
cs.CV2018★ 8 cited
Characterizing multiple instance datasets
Veronika Cheplygina, David M. J. Tax
In many pattern recognition problems, a single feature vector is not sufficient to describe an object. In multiple instance learning (MIL), objects are represented by sets (\emph{b…
cs.CV2018★ 1 cited
Unsupervised Learning of Sequence Representations by Autoencoders
Wenjie Pei, David M. J. Tax
Sequence data is challenging for machine learning approaches, because the lengths of the sequences may vary between samples. In this paper, we present an unsupervised learning mode…