Gavin Brown

Irene W. Y. Ma, S. Millington, L. Devine, 2016, Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine.

Exploring sketches for probability estimation with sublinear memory

Gavin Brown, Anthony Kleerekoper, Mikel Luján, 2013, 2013 IEEE International Conference on Big Data.

A Study of Semi-supervised Generative Ensembles

Gavin Brown, Manuela Zanda, Gavin Brown, 2009, MCS.

Minimum Heart Rates of Marsupials

Gavin Brown, J. E. Kinnear, G. Brown, 1967, Nature.

Managing Diversity in Regression Ensembles

Peter Tiño, Gavin Brown, Jeremy L. Wyatt, 2005, J. Mach. Learn. Res..

The influence of expertise on perceived and actual household disaster preparedness

A. Largey, Gavin Brown, C. McMullan, 2021 .

Cost-sensitive boosting algorithms: Do we really need them?

Peter A. Flach, Narayanan Unny Edakunni, Gavin Brown, 2016, Machine Learning.

Geographies of PrEP, TasP and undetectability: Reconceptualising HIV assemblages to explore what else matters in the lives of gay and bisexual men

C. D. Feliciantonio, Gavin Brown, C. Feliciantonio, 2021, Dialogues in Human Geography.

Distinguishing prognostic and predictive biomarkers: an information theoretic approach

Gavin Brown, James Weatherall, Konstantinos Sechidis, 2018, Bioinform..

The biology of marsupials of the Australian arid zone.

Gavin Brown, 1974, Australian Mammalogy.

Predicting Performance of OWL Reasoners: Locally or Globally?

Gavin Brown, Ulrike Sattler, Viachaslau Sazonau, 2014, KR.

Predicting OWL Reasoners: Locally or Globally?

Gavin Brown, Ulrike Sattler, Viachaslau Sazonau, 2014, Description Logics.

Conditional Likelihood Maximisation: A Unifying Framework for Information Theoretic Feature Selection

Gavin Brown, Mikel Luján, Adam Craig Pocock, 2012, J. Mach. Learn. Res..

Statistical Hypothesis Testing in Positive Unlabelled Data

Gavin Brown, Borja Calvo, Konstantinos Sechidis, 2014, ECML/PKDD.

A New Perspective for Information Theoretic Feature Selection

Gavin Brown, Gavin Brown, 2009, AISTATS.

Dealing with under-reported variables: An information theoretic solution

Gavin Brown, Mikel Luján, Matthew Sperrin, 2017, Int. J. Approx. Reason..

Modelling 3D Topographic Space Against Indoor Navigation Requirements

Gavin Brown, Sisi Zlatanova, Thomas H. Kolbe, 2013 .

Is Feature Selection Secure against Training Data Poisoning?

Claudia Eckert, Gavin Brown, Fabio Roli, 2015, ICML.

Towards Cross-Platform Portability of Coupled-Cluster Methods with Perturbative Triples using SYCL

Gavin Brown, Abhishek Bagusetty, A. Panyala, 2022, 2022 IEEE/ACM International Workshop on Performance, Portability and Productivity in HPC (P3HPC).

Electronic Properties of Imidazole

Gavin Brown, G. P. Brown, S. Aftergut, 1961, Nature.

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

Gavin Brown, Fabio Roli, Marco Melis, 2017, 2017 IEEE International Conference on Computer Vision Workshops (ICCVW).

"Good" and "Bad" Diversity in Majority Vote Ensembles

Gavin Brown, Ludmila I. Kuncheva, L. Kuncheva, 2010, MCS.

Measuring the Stability of Feature Selection with Applications to Ensemble Methods

Gavin Brown, Sarah Nogueira, Gavin Brown, 2015, MCS.

Learn++.MF: A random subspace approach for the missing feature problem

Gavin Brown, Robi Polikar, Ludmila I. Kuncheva, 2010, Pattern Recognit..

Calibrating AdaBoost for Asymmetric Learning

Gavin Brown, Nikolaos Nikolaou, N. Nikolaou, 2015, MCS.

Boosting Java Performance Using GPGPUs pdf

Gavin Brown, Mikel Luján, Christos Kotselidis, 2015, ARCS.

Informative Priors for Markov Blanket Discovery

Gavin Brown, Mikel Luján, Adam Craig Pocock, 2012, AISTATS.

Orange Soil from the Moon

J. G. Holland, Gavin Brown, A. Peckett, 1973, Nature.

On the Use of Spearman's Rho to Measure the Stability of Feature Rankings

Gavin Brown, Konstantinos Sechidis, Sarah Nogueira, 2017, IbPRIA.

Exploiting ensemble diversity for automatic feature extraction

Heiko Wersing, Bernhard Sendhoff, Gavin Brown, 2002, Proceedings of the 9th International Conference on Neural Information Processing, 2002. ICONIP '02..

VAR planning using partitioned power system networks

R. Adapa, J. A. Momoh, G. F. Brown, 1993, Proceedings of 36th Midwest Symposium on Circuits and Systems.

The Use of the Ambiguity Decomposition in Neural Network Ensemble Learning Methods

Gavin Brown, Jeremy L. Wyatt, J. Wyatt, 2003, ICML.

Gradient Boosting Models for Photovoltaic Power Estimation Under Partial Shading Conditions

Gavin Brown, Efstratios I. Batzelis, Nikolaos Nikolaou, 2017, DARE@PKDD/ECML.

Selective Volatilization on the Lunar Surface: Evidence from Apollo 14 Feldspar-Phyric Basalts

Gavin Brown, A. Peckett, 1971, Nature.

Picrite basalts, ferrobasalts, feldspathic norites, and rhyolites in a strongly fractionated lunar crust

Gavin Brown, C. H. Emeleus, A. Peckett, 1971 .

Markov Blanket Discovery in Positive-Unlabelled and Semi-supervised Data

Gavin Brown, Konstantinos Sechidis, Konstantinos Sechidis, 2015, ECML/PKDD.

Products of Random Variables and Kakutani's Criterion for Orthogonality of Product Measures

W. Moran, Gavin Brown, 1975 .

REFINEMENT OF TRICLINIC LYSOZYME

L. Sieker, Gavin Brown, L. H. Jensen, 1985 .

Molecular Orbital Studies of Nitrosyl Metalloporphyrin Complexes

Gavin Brown, J. Graham, 2001 .

Between Two Extremes: Examining Decompositions of the Ensemble Objective Function

Gavin Brown, Ping Sun, Jeremy L. Wyatt, 2005, Multiple Classifier Systems.

Modular Dimensionality Reduction

Tingting Mu, Gavin Brown, Henry W. J. Reeve, 2018, ECML/PKDD.

Using Static Code Features for Intelligent Squash Prediction

Adam Craig Pocock, M. Luján, Jeremy Singer, 2009 .

Joint Training of Neural Network Ensembles pdf

Gavin Brown, Andrew M. Webb, Mikel Luján, 2019, ArXiv.

Deep learning-based classification and anomaly detection of side-channel signals

Gavin Brown, Quan Zhou, John Wang, 2018, Defense + Security.

Insights into distributed feature ranking

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Gavin Brown, 2019, Inf. Sci..

Towards intelligent analysis techniques for object pretenuring

Gavin Brown, Jeremy Singer, Mikel Luján, 2007, PPPJ.

Garbage collection auto-tuning for Java mapreduce on multi-cores

Gavin Brown, Jeremy Singer, Mikel Luján, 2011, ISMM '11.

Intelligent selection of application-specific garbage collectors

Gavin Brown, Jeremy Singer, John Cavazos, 2007, ISMM '07.

On the Stability of Feature Selection Algorithms

Gavin Brown, Konstantinos Sechidis, Sarah Nogueira, 2017, J. Mach. Learn. Res..

Diversity and degrees of freedom in regression ensembles

Gavin Brown, Henry W. J. Reeve, Gavin Brown, 2018, Neurocomputing.

Efficient feature selection using shrinkage estimators

Gavin Brown, Adam Pocock, Laura Azzimonti, 2019, Machine Learning.

To Ensemble or Not Ensemble: When Does End-to-End Training Fail?

Henry W. J. Reeve, Wenlin Chen, M. Luján, 2020, ECML/PKDD.

Measuring the Stability of Feature Selection

Gavin Brown, Sarah Nogueira, Gavin Brown, 2016, ECML/PKDD.

Stress indicators in minorities with multiple sclerosis.

Gavin Brown, M. A. Hanks, Evelyn A. Hunter, 2023, Multiple sclerosis and related disorders.

Toward an Understanding of Adversarial Examples in Clinical Trials

Gavin Brown, James Weatherall, Konstantinos Sechidis, 2018, ECML/PKDD.

Beyond Fano's inequality: bounds on the optimal F-score, BER, and cost-sensitive risk and their implications

Narayanan Unny Edakunni, Gavin Brown, Adam Craig Pocock, 2013, J. Mach. Learn. Res..

Bayesian estimation of rule accuracy in UCS

Gavin Brown, Tim Kovacs, James A. R. Marshall, 2007, GECCO '07.

Random Projection Random Discretization Ensembles—Ensembles of Linear Multivariate Decision Trees

Gavin Brown, Amir Ahmad, Gavin Brown, 2014, IEEE Transactions on Knowledge and Data Engineering.

Compiler-Driven Software Speculation for Thread-Level Parallelism

Gavin Brown, Mikel Luján, Paraskevas Yiapanis, 2015, ACM Trans. Program. Lang. Syst..

The K-Nearest Neighbour UCB Algorithm for Multi-Armed Bandits with Covariates pdf

Gavin Brown, Henry W. J. Reeve, Joseph C. Mellor, 2018, ALT.

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

Gavin Brown, Henry W. J. Reeve, Gavin Brown, 2017, ALT.

Branch Prediction with Bayesian Networks

Gavin Brown, Jeremy Singer, Ian Watson, 2007 .

Analytic Solutions to Differential Equations under Graph-Based Genetic Programming

Gavin Brown, Julian Francis Miller, Tom Seaton, 2010, EuroGP.

Return Value Prediction meets Information Theory

Gavin Brown, Jeremy Singer, Jeremy Singer, 2006, QAPL.

Learn++.MF: A random subspace approach for the missing feature problem

R. Polikar, L. Kuncheva, Gavin Brown, 2010, Pattern Recognition.

Fundamental Nano-Patterns to Characterize and Classify Java Methods

Gavin Brown, Jeremy Singer, Mikel Luján, 2010, LDTA.

Psychosocial Intervention

Gavin Brown, Emily Turner, Juanjo Medina-Ariza, 2022 .

Random Ordinality Ensembles: Ensemble methods for multi-valued categorical data

Gavin Brown, Amir Ahmad, Gavin Brown, 2015, Inf. Sci..

Random Ordinality Ensembles A Novel Ensemble Method for Multi-valued Categorical Data

Gavin Brown, Amir Ahmad, Gavin Brown, 2009, MCS.

To Ensemble or Not Ensemble: When Does End-to-End Training Fail?

Henry W. J. Reeve, Wenlin Chen, M. Luján, 2020, ECML/PKDD.

Information Theoretic Feature Selection in Multi-label Data through Composite Likelihood

Gavin Brown, Konstantinos Sechidis, Nikolaos Nikolaou, 2014, S+SSPR.