Efficient feature selection using shrinkage estimators [PDF][Correction]
Konstantinos Sechidis, Laura Azzimonti, Adam Pocock, Giorgio Corani, James Weatherall, Gavin Brown
Machine Learning Journal (MLJ). Volume 108, Pages 1261-1286, 2019.
The statement and proof of Theorem 3.1 was corrected in 2020.
Correction appeared in Machine Learning Journal (MLJ). Volume 109, Pages 1565-1567, 2020.

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, 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, 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. There is an updated version of FEAST available on GitHub.


Minimally-Constrained Multilingual Word Embeddings via Artificial-Code Switching   [PDF]
Michael Wick, Pallika Kanani, Adam Pocock
Thirtieth AAAI conference on Artificial Intelligence (AAAI). Phoenix, February 2016.

A Scalable Implementation of Information Theoretic Feature Selection for High Dimensional Data   [PDF]
Anthony Kleerekoper, Michael Pappas, Adam Pocock, Gavin Brown, Mikel Luján
IEEE Intl Conference on Big Data. Santa Clara, October 2015.

Augur: Data-Parallel Probabilistic Modeling   [PDF] [Paper page]
Jean-Baptiste Tristan, Daniel Huang, Joseph Tassarotti, Adam Pocock, Stephen Green, Guy Steele
Neural Information Processing Systems (NIPS). Montreal, December 2014.
Published in Advances in Neural Information Processing Systems, Volume 27, Pages 2600-2608.

Informative Priors for Markov Blanket Discovery   [PDF] [Supplementary Material] [Poster]
Adam Pocock, Mikel Luján, 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, 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.
This paper was updated on 05-02-2017 to correct an issue with Algorithm 1. The original version set h prime to arg max instead of arg min.


Minimally-Constrained Multilingual Word Embeddings via Artificial-Code Switching   [PDF]
Michael Wick, Pallika Kanani, Adam Pocock
Multi-task and Transfer Learning workshop, NIPS. Montreal, December 2015.

Attribute Extraction from Noisy Text Using Character-based Sequence Tagging Models   [PDF]
Pallika Kanani, Michael Wick, Adam Pocock
Machine Learning for eCommerce workshop, NIPS. Montreal, December 2015.


Detecting and Exorcising Statistical Demons from Language Models with Anti-Models of Negative Data   [PDF][ArXiv]
Michael Wick, Kate Silverstein, Jean-Baptiste Tristan, Adam Pocock, Mark Johnson
ArXiv 2010.11855, October 2020.

PhD Thesis

Feature Selection via Joint Likelihood  [PDF]
Adam Pocock
Supervisors: Gavin Brown, Mikel Luján
University of Manchester. August 2012.
Awarded the 2013 BCS Distinguished Dissertation prize.

MSc Thesis

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