Gavin Brown

	2012
33		Gavin Brown, Alexander M. Kasprzyk: Small polygons and toric codes CoRR abs/1204.0248: (2012)
32		Gavin Brown, Adam Pocock, Ming-Jie Zhao, Mikel Luján: Conditional Likelihood Maximisation: A Unifying Framework for Information Theoretic Feature Selection. Journal of Machine Learning Research 13: 27-66 (2012)
31		Adam Pocock, Mikel Luján, Gavin Brown: Informative Priors for Markov Blanket Discovery. Journal of Machine Learning Research - Proceedings Track 22: 905-913 (2012)
	2011
30		Tim Kovacs, Narayanan Unny Edakunni, Gavin Brown: Accuracy exponentiation in UCS and its effect on voting margins. GECCO 2011: 1251-1258
29		Narayanan Unny Edakunni, Gavin Brown, Tim Kovacs: Online, GA based mixture of experts: a probabilistic model of ucs. GECCO 2011: 1267-1274
28		Jeremy Singer, George Kovoor, Gavin Brown, Mikel Luján: Garbage collection auto-tuning for Java mapreduce on multi-cores. ISMM 2011: 109-118
	2010
27		Tom Seaton, Gavin Brown, Julian F. Miller: Analytic Solutions to Differential Equations under Graph-Based Genetic Programming. EuroGP 2010: 232-243
26		Jeremy Singer, Richard E. Jones, Gavin Brown, Mikel Luján: The economics of garbage collection. ISMM 2010: 103-112
25		Gavin Brown, Ludmila I. Kuncheva: "Good" and "Bad" Diversity in Majority Vote Ensembles. MCS 2010: 124-133
24		Adam Pocock, Paraskevas Yiapanis, Jeremy Singer, Mikel Luján, Gavin Brown: Online Non-stationary Boosting. MCS 2010: 205-214
23		Gavin Brown: Some Thoughts at the Interface of Ensemble Methods and Feature Selection. MCS 2010: 314
22		Gavin Brown: Ensemble Learning. Encyclopedia of Machine Learning 2010: 312-320
21		Jeremy Singer, Gavin Brown, Mikel Luján, Adam Pocock, Paraskevas Yiapanis: Fundamental Nano-Patterns to Characterize and Classify Java Methods. Electr. Notes Theor. Comput. Sci. 253(7): 191-204 (2010)
20		Robi Polikar, Joseph DePasquale, Hussein Syed Mohammed, Gavin Brown, Ludmila I. Kuncheva: Learn++.MF: A random subspace approach for the missing feature problem. Pattern Recognition 43(11): 3817-3832 (2010)
	2009
19		Narayanan Unny Edakunni, Tim Kovacs, Gavin Brown, James A. R. Marshall: Modeling UCS as a mixture of experts. GECCO 2009: 1187-1194
18		Amir Ahmad, Gavin Brown: Random Ordinality Ensembles A Novel Ensemble Method for Multi-valued Categorical Data. MCS 2009: 222-231
17		Manuela Zanda, Gavin Brown: A Study of Semi-supervised Generative Ensembles. MCS 2009: 242-251
16		Gavin Brown: An Information Theoretic Perspective on Multiple Classifier Systems. MCS 2009: 344-353
15		Amir Ahmad, Gavin Brown: A Study of Random Linear Oracle Ensembles. MCS 2009: 488-497
14		Gavin Brown: A New Perspective for Information Theoretic Feature Selection. Journal of Machine Learning Research - Proceedings Track 5: 49-56 (2009)
	2007
13		Gavin Brown, Tim Kovacs, James A. R. Marshall: UCSpv: principled voting in UCS rule populations. GECCO 2007: 1774-1781
12		James A. R. Marshall, Gavin Brown, Tim Kovacs: Bayesian estimation of rule accuracy in UCS. GECCO (Companion) 2007: 2831-2834
11		Jeremy Singer, Gavin Brown, Ian Watson, John Cavazos: Intelligent selection of application-specific garbage collectors. ISMM 2007: 91-102
10		Manuela Zanda, Gavin Brown, Giorgio Fumera, Fabio Roli: Ensemble Learning in Linearly Combined Classifiers Via Negative Correlation. MCS 2007: 440-449
9		Jeremy Singer, Gavin Brown, Mikel Luján, Ian Watson: Towards intelligent analysis techniques for object pretenuring. PPPJ 2007: 203-208
	2006
8		Jeremy Singer, Gavin Brown: Return Value Prediction meets Information Theory. Electr. Notes Theor. Comput. Sci. 164(3): 137-151 (2006)
	2005
7		Gavin Brown, Jeremy L. Wyatt, Ping Sun: Between Two Extremes: Examining Decompositions of the Ensemble Objective Function. Multiple Classifier Systems 2005: 296-305
6		Gavin Brown, Jeremy L. Wyatt, Rachel Harris, Xin Yao: Diversity creation methods: a survey and categorisation. Information Fusion 6(1): 5-20 (2005)
5		Gavin Brown, Jeremy L. Wyatt, Peter Tino: Managing Diversity in Regression Ensembles. Journal of Machine Learning Research 6: 1621-1650 (2005)
	2003
4		Gavin Brown, Jeremy L. Wyatt: The Use of the Ambiguity Decomposition in Neural Network Ensemble Learning Methods. ICML 2003: 67-74
3		Gavin Brown, Jeremy L. Wyatt: Negative Correlation Learning and the Ambiguity Family of Ensemble Methods. Multiple Classifier Systems 2003: 266-275
	2002
2		Gavin Brown, Dai Feng, Sun Yong Sheng: Kolmogorov Width of Classes of Smooth Functions on the Sphere Sd-1. J. Complexity 18(4): 1001-1023 (2002)
	2001
1		Gavin Brown: Datagraphs in Algebraic Geometry and K3 Surfaces. SNSC 2001: 210-224

Coauthor Index

1	Amir Ahmad	[15] [18]
2	John Cavazos	[11]
3	Joseph DePasquale	[20]
4	Narayanan Unny Edakunni	[19] [29] [30]
5	Dai Feng	[2]
6	Giorgio Fumera	[10]
7	Rachel Harris	[6]
8	Richard E. Jones	[26]
9	Alexander M. Kasprzyk	[33]
10	Tim Kovacs	[12] [13] [19] [29] [30]
11	George Kovoor	[28]
12	Ludmila I. Kuncheva (Ludmila Kuncheva)	[20] [25]
13	Mikel Luján	[9] [21] [24] [26] [28] [31] [32]
14	James A. R. Marshall	[12] [13] [19]
15	Julian Francis Miller (Julian F. Miller)	[27]
16	Hussein Syed Mohammed	[20]
17	Adam Pocock	[21] [24] [31] [32]
18	Robi Polikar	[20]
19	Fabio Roli	[10]
20	Tom Seaton	[27]
21	Sun Yong Sheng	[2]
22	Jeremy Singer	[8] [9] [11] [21] [24] [26] [28]
23	Ping Sun	[7]
24	Peter Tiño (Peter Tino)	[5]
25	Ian Watson	[9] [11]
26	Jeremy L. Wyatt	[3] [4] [5] [6] [7]
27	Xin Yao	[6]
28	Paraskevas Yiapanis	[21] [24]
29	Manuela Zanda	[10] [17]
30	Ming-Jie Zhao	[32]

Colors in the list of coauthors

Last update Sun May 27 04:04:01 2012 CET by the DBLP Team — Data released under the ODC-BY 1.0 license — See also our legal information page