Publications

Beyond Fano’s Inequality: Bounds on the Optimal F-Score, BER, and Cost-Sensitive Risk and Their Implications [PDF]
Ming-Jie Zhao, Narayanan Edakunni, Adam Pocock, and Gavin Brown
Journal of Machine Learning Research (JMLR). Volume 14, Pages 1033-1090, 2013.

Conditional Likelihood Maximisation: A Unifying Framework for Information Theoretic Feature Selection [PDF][Poster]
Gavin Brown, Adam Pocock, Ming-Jie Zhao, and Mikel Luján
Journal of Machine Learning Research (JMLR). Volume 13, Pages 27-66, 2012.
The paper is available here and the code for the various feature selection algorithms is on mloss or locally hosted here.

Informative Priors for Markov Blanket Discovery   [PDF] [Supplementary Material] [Poster]
Adam Pocock, Mikel Luján, and Gavin Brown
15th Intl Conference on Artificial Intelligence and Statistics (AISTATS). La Palma, April 2012.
Published in JMLR W&CP, Volume 22, Pages 905-913.

Online Nonstationary Boosting  [PDF]
Adam Pocock, Paraskevas Yiapanis, Jeremy Singer, Mikel Luján, and Gavin Brown
9th Intl Workshop on Multiple Classifier Systems (MCS). Cairo, April 2010
doi: 10.1007/978-3-642-12127-2_21
A Java implementation of Online Boosting and ONSBoost is found here

Feature Selection via Joint Likelihood  [PDF]
Adam Pocock
Supervisors: Gavin Brown, Mikel Luján
University of Manchester. August 2012

Feature Selection using Information Theoretic Techniques  [PDF]
Adam Pocock
Supervisor: Gavin Brown
University of Manchester. September 2008