Mark Girolami

2008
53	EE	Nicola Lama, Mark Girolami: vbmp: Variational Bayesian Multinomial Probit Regression for multi-class classification in R. Bioinformatics 24(1): 135-136 (2008)
52	EE	Vladislav Vyshemirsky, Mark Girolami: Bayesian ranking of biochemical system models. Bioinformatics 24(6): 833-839 (2008)
2007
51	EE	Oliver Sharma, Mark Girolami, Joseph S. Sventek: Detecting worm variants using machine learning. CoNEXT 2007: 2
50	EE	Dongshan Xing, Mark Girolami: Employing Latent Dirichlet Allocation for fraud detection in telecommunications. Pattern Recognition Letters 28(13): 1727-1734 (2007)
49	EE	S. Manocha, Mark Girolami: An empirical analysis of the probabilistic K-nearest neighbour classifier. Pattern Recognition Letters 28(13): 1818-1824 (2007)
2006
48	EE	Gavin C. Cawley, Nicola L. C. Talbot, Mark Girolami: Sparse Multinomial Logistic Regression via Bayesian L1 Regularisation. NIPS 2006: 209-216
47	EE	Mark Girolami, Mingjun Zhong: Data Integration for Classification Problems Employing Gaussian Process Priors. NIPS 2006: 465-472
46	EE	Robert Jenssen, Torbjørn Eltoft, Mark Girolami, Deniz Erdogmus: Kernel Maximum Entropy Data Transformation and an Enhanced Spectral Clustering Algorithm. NIPS 2006: 633-640
45	EE	Anna Szymkowiak-Have, Mark Girolami, Jan Larsen: Clustering via kernel decomposition. IEEE Transactions on Neural Networks 17(1): 256-264 (2006)
44	EE	Mark Girolami, Simon Rogers: Variational Bayesian Multinomial Probit Regression with Gaussian Process Priors. Neural Computation 18(8): 1790-1817 (2006)
2005
43	EE	Simon Rogers, Mark Girolami, Ronald Krebs, Harald Mischak: Disease Classification from Capillary Electrophoresis: Mass Spectrometry. ICAPR (1) 2005: 183-191
42	EE	Mark Girolami, Simon Rogers: Hierarchic Bayesian models for kernel learning. ICML 2005: 241-248
41	EE	Leif Azzopardi, Mark Girolami, Malcolm Crowe: Probabilistic hyperspace analogue to language. SIGIR 2005: 575-576
40	EE	Simon Rogers, Mark Girolami: A Bayesian regression approach to the inference of regulatory networks from gene expression data. Bioinformatics 21(14): 3131-3137 (2005)
39	EE	Mark Girolami, Ata Kabán: Sequential Activity Profiling: Latent Dirichlet Allocation of Markov Chains. Data Min. Knowl. Discov. 10(3): 175-196 (2005)
38	EE	Simon Rogers, Mark Girolami, Colin Campbell, Rainer Breitling: The Latent Process Decomposition of cDNA Microarray Data Sets. IEEE/ACM Trans. Comput. Biology Bioinform. 2(2): 143-156 (2005)
2004
37	EE	Ali Al-Shahib, Chao He, Aik Choon Tan, Mark Girolami, David Gilbert: An Assessment of Feature Relevance in Predicting Protein Function from Sequence. IDEAL 2004: 52-57
36	EE	Leif Azzopardi, Mark Girolami, Cornelis Joost van Rijsbergen: User biased document language modelling. SIGIR 2004: 542-543
35	EE	Mark Girolami, Rainer Breitling: Biologically valid linear factor models of gene expression. Bioinformatics 20(17): 3021-3033 (2004)
34	EE	Chao He, Mark Girolami, Gary Ross: Employing optimized combinations of one-class classifiers for automated currency validation. Pattern Recognition 37(6): 1085-1096 (2004)
33	EE	Chao He, Mark Girolami: Novelty detection employing an L2 optimal non-parametric density estimator. Pattern Recognition Letters 25(12): 1389-1397 (2004)
2003
32	EE	Mark Girolami, Ata Kabán: Simplicial Mixtures of Markov Chains: Distributed Modelling of Dynamic User Profiles. NIPS 2003
31	EE	Leif Azzopardi, Mark Girolami, Keith van Risjbergen: Investigating the relationship between language model perplexity and IR precision-recall measures. SIGIR 2003: 369-370
30	EE	Mark Girolami, Ata Kabán: On an equivalence between PLSI and LDA. SIGIR 2003: 433-434
29	EE	Mark Girolami, Chao He: Probability Density Estimation from Optimally Condensed Data Samples. IEEE Trans. Pattern Anal. Mach. Intell. 25(10): 1253-1264 (2003)
28		Ella Bingham, Ata Kabán, Mark Girolami: Topic Identification in Dynamical Text by Complexity Pursuit. Neural Processing Letters 17(1): 69-83 (2003)
2002
27		Fabio Crestani, Mark Girolami, C. J. van Rijsbergen: Advances in Information Retrieval, 24th BCS-IRSG European Colloquium on IR Research Glasgow, UK, March 25-27, 2002 Proceedings Springer 2002
26	EE	Ata Kabán, Peter Tiño, Mark Girolami: A General Framework for a Principled Hierarchical Visualization of Multivariate Data. IDEAL 2002: 518-523
25		Ata Kabán, Mark Girolami: A Dynamic Probabilistic Model to Visualise Topic Evolution in Text Streams. J. Intell. Inf. Syst. 18(2-3): 107-125 (2002)
24		Alexei Vinokourov, Mark Girolami: A Probabilistic Framework for the Hierarchic Organisation and Classification of Document Collections. J. Intell. Inf. Syst. 18(2-3): 153-172 (2002)
23	EE	Mark Girolami: Orthogonal Series Density Estimation and the Kernel Eigenvalue Problem. Neural Computation 14(3): 669-688 (2002)
22		Ata Kabán, Mark Girolami: Fast Extraction of Semantic Features from a Latent Semantic Indexed Text Corpus. Neural Processing Letters 15(1): 31-43 (2002)
21	EE	Mark Girolami: Latent variable models for the topographic organisation of discrete and strictly positive data. Neurocomputing 48(1-4): 185-198 (2002)
20	EE	Fabio Crestani, Mark Girolami, C. J. van Rijsbergen: Report on the 24th European colloquium on information retrieval research (ECIR 2002). SIGIR Forum 36(1): 6-9 (2002)
19	EE	Fabio Crestani, Mark Girolami: Report on the 24th European Colloquium on Information Retrieval Research. SIGMOD Record 31(3): 77-80 (2002)
2001
18	EE	Ella Bingham, Ata Kabán, Mark Girolami: Finding Topics in Dynamical Text: Application to Chat Line Discussions. WWW Posters 2001
17	EE	Ata Kabán, Mark Girolami: A Combined Latent Class and Trait Model for the Analysis and Visualization of Discrete Data. IEEE Trans. Pattern Anal. Mach. Intell. 23(8): 859-872 (2001)
16	EE	Mark Girolami: A Variational Method for Learning Sparse and Overcomplete Representations. Neural Computation 13(11): 2517-2532 (2001)
15		Roman Rosipal, Mark Girolami: An Expectation-Maximization Approach to Nonlinear Component Analysis. Neural Computation 13(3): 505-510 (2001)
14	EE	Roman Rosipal, Mark Girolami, Leonard J. Trejo, Andrzej Cichocki: Kernel PCA for Feature Extraction and De-Noising in Nonlinear Regression. Neural Computing and Applications 10(3): 231-243 (2001)
2000
13	EE	Mark Girolami, Alexei Vinokourov, Ata Kabán: The Organization and Visualization of Document Corpora: A Probabilistic Approach. DEXA Workshop 2000: 558-564
12	EE	Mark Girolami: A generative model for sparse discrete binary data with non-uniform categorical priors. ESANN 2000: 1-6
11	EE	Alexei Vinokourov, Mark Girolami: Probabilistic Hierarchical Clustering Method for Organizing Collections of Text Documents. ICPR 2000: 2182-2185
10	EE	Ata Kabán, Mark Girolami: Initialized and Guided EM-Clustering of Sparse Binary Data with Application to Text Based Documents. ICPR 2000: 2744-2747
1999
9		Te-Won Lee, Mark Girolami, Terrence J. Sejnowski: Independent Component Analysis Using an Extended Infomax Algorithm for Mixed Sub-Gaussian and Super-Gaussian Sources. Neural Computation 11(2): 417-441 (1999)
1998
8	EE	Mark Girolami, Andrzej Cichocki, Shun-ichi Amari: A common neural-network model for unsupervised exploratory data analysis and independent component analysis. IEEE Transactions on Neural Networks 9(6): 1495-1501 (1998)
7		Mark Girolami: An Alternative Perspective on Adaptive Independent Component Analysis Algorithms. Neural Computation 10(8): 2103-2114 (1998)
6		Mark Girolami: The Latent Variable Data Model for Exploratory Data Analysis and Visualisation: A Generalisation of the Nonlinear Infomax Algorithm. Neural Processing Letters 8(1): 27-39 (1998)
5	EE	Mark Girolami: A nonlinear model of the binaural cocktail party effect. Neurocomputing 22(1-3): 201-215 (1998)
1997
4		Mark Girolami, Colin Fyfe: Independence is far from normal. ESANN 1997
3	EE	Mark Girolami, Colin Fyfe: Stochastic ICA Contrast Maximisation Using Oja's Nonlinear PCA Algorithm. Int. J. Neural Syst. 8(5-6): 661-678 (1997)
2	EE	Mark Girolami, Colin Fyfe: An extended exploratory projection pursuit network with linear and nonlinear anti-hebbian lateral connections applied to the cocktail party problem. Neural Networks 10(9): 1607-1618 (1997)
1996
1		Mark Girolami, Colin Fyfe: A Temporal Model of Linear Anti-Hebbian Learning. Neural Processing Letters 4(3): 139-148 (1996)

Coauthor Index

1	Ali Al-Shahib	[37]
2	Shun-ichi Amari	[8]
3	Leif Azzopardi	[31] [36] [41]
4	Ella Bingham	[18] [28]
5	Rainer Breitling	[35] [38]
6	Colin Campbell	[38]
7	Gavin C. Cawley	[48]
8	Andrzej Cichocki	[8] [14]
9	Fabio Crestani	[19] [20] [27]
10	Malcolm Crowe	[41]
11	Torbjørn Eltoft	[46]
12	Deniz Erdogmus	[46]
13	Colin Fyfe	[1] [2] [3] [4]
14	David Gilbert (David R. Gilbert)	[37]
15	Chao He	[29] [33] [34] [37]
16	Robert Jenssen	[46]
17	Ata Kabán (Ata Kaban)	[10] [13] [17] [18] [22] [25] [26] [28] [30] [32] [39]
18	Ronald Krebs	[43]
19	Nicola Lama	[53]
20	Jan Larsen	[45]
21	Te-Won Lee	[9]
22	S. Manocha	[49]
23	Harald Mischak	[43]
24	C. J. van Rijsbergen (Cornelis Joost van Rijsbergen, Keith van Rijsbergen)	[20] [27] [36]
25	Keith van Risjbergen	[31]
26	Simon Rogers	[38] [40] [42] [43] [44]
27	Roman Rosipal	[14] [15]
28	Gary Ross	[34]
29	Terrence J. Sejnowski	[9]
30	Oliver Sharma	[51]
31	Joseph S. Sventek (Joe Sventek)	[51]
32	Anna Szymkowiak-Have	[45]
33	Nicola L. C. Talbot	[48]
34	Aik Choon Tan	[37]
35	Peter Tiño (Peter Tino)	[26]
36	Leonard J. Trejo	[14]
37	Alexei Vinokourov	[11] [13] [24]
38	Vladislav Vyshemirsky	[52]
39	Dongshan Xing	[50]
40	Mingjun Zhong	[47]

Colors in the list of coauthors