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Note: Links lead to the DBLP on the Web. Mark Girolami Simon Rogers , Mark Girolami, Ronald Krebs , Harald Mischak : Disease Classification from Capillary Electrophoresis: Mass Spectrometry. ICAPR (1) 2005 : 183-191 Mark Girolami, Simon Rogers : Hierarchic Bayesian models for kernel learning. ICML 2005 : 241-248 Leif Azzopardi , Mark Girolami, Malcolm Crowe : Probabilistic hyperspace analogue to language. SIGIR 2005 : 575-576 Simon Rogers , Mark Girolami: A Bayesian regression approach to the inference of regulatory networks from gene expression data. Bioinformatics 21 (14): 3131-3137 (2005) Mark Girolami, Ata Kabán : Sequential Activity Profiling: Latent Dirichlet Allocation of Markov Chains. Data Min. Knowl. Discov. 10 (3): 175-196 (2005) 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) 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 Leif Azzopardi , Mark Girolami, Cornelis Joost van Rijsbergen : User biased document language modelling. SIGIR 2004 : 542-543 Mark Girolami, Rainer Breitling : Biologically valid linear factor models of gene expression. Bioinformatics 20 (17): 3021-3033 (2004) Chao He , Mark Girolami, Gary Ross : Employing optimized combinations of one-class classifiers for automated currency validation. Pattern Recognition 37 (6): 1085-1096 (2004) Chao He , Mark Girolami: Novelty detection employing an L2 optimal non-parametric density estimator. Pattern Recognition Letters 25 (12): 1389-1397 (2004) Mark Girolami, Ata Kabán : Simplicial Mixtures of Markov Chains: Distributed Modelling of Dynamic User Profiles. NIPS 2003 Leif Azzopardi , Mark Girolami, Keith van Risjbergen : Investigating the relationship between language model perplexity and IR precision-recall measures. SIGIR 2003 : 369-370 Mark Girolami, Ata Kabán : On an equivalence between PLSI and LDA. SIGIR 2003 : 433-434 Mark Girolami, Chao He : Probability Density Estimation from Optimally Condensed Data Samples. IEEE Trans. Pattern Anal. Mach. Intell. 25 (10): 1253-1264 (2003) Ella Bingham , Ata Kabán , Mark Girolami: Topic Identification in Dynamical Text by Complexity Pursuit. Neural Processing Letters 17 (1): 69-83 (2003) 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 Ata Kabán , Peter Tiño , Mark Girolami: A General Framework for a Principled Hierarchical Visualization of Multivariate Data. IDEAL 2002 : 518-523 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) 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) Mark Girolami: Orthogonal Series Density Estimation and the Kernel Eigenvalue Problem. Neural Computation 14 (3): 669-688 (2002) Ata Kabán , Mark Girolami: Fast Extraction of Semantic Features from a Latent Semantic Indexed Text Corpus. Neural Processing Letters 15 (1): 31-43 (2002) Mark Girolami: Latent variable models for the topographic organisation of discrete and strictly positive data. Neurocomputing 48 (1-4): 185-198 (2002) 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) Fabio Crestani , Mark Girolami: Report on the 24th European Colloquium on Information Retrieval Research. SIGMOD Record 31 (3): 77-80 (2002) Ella Bingham , Ata Kabán , Mark Girolami: Finding Topics in Dynamical Text: Application to Chat Line Discussions. WWW Posters 2001 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) Mark Girolami: A Variational Method for Learning Sparse and Overcomplete Representations. Neural Computation 13 (11): 2517-2532 (2001) Roman Rosipal , Mark Girolami: An Expectation-Maximization Approach to Nonlinear Component Analysis. Neural Computation 13 (3): 505-510 (2001) 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) Mark Girolami, Alexei Vinokourov , Ata Kabán : The Organization and Visualization of Document Corpora: A Probabilistic Approach. DEXA Workshop 2000 : 558-564 Alexei Vinokourov , Mark Girolami: Probabilistic Hierarchical Clustering Method for Organizing Collections of Text Documents. ICPR 2000 : 2182-2185 Ata Kabán , Mark Girolami: Initialized and Guided EM-Clustering of Sparse Binary Data with Application to Text Based Documents. ICPR 2000 : 2744-2747 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) Mark Girolami: An Alternative Perspective on Adaptive Independent Component Analysis Algorithms. Neural Computation 10 (8): 2103-2114 (1998) 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) Mark Girolami: A nonlinear model of the binaural cocktail party effect. Neurocomputing 22 (1-3): 201-215 (1998) Mark Girolami, Colin Fyfe : Independence is far from normal. ESANN 1997 Mark Girolami, Colin Fyfe : Stochastic ICA Contrast Maximisation Using Oja's Nonlinear PCA Algorithm. Int. J. Neural Syst. 8 (5-6): 661-678 (1997) 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) Mark Girolami, Colin Fyfe : A Temporal Model of Linear Anti-Hebbian Learning. Neural Processing Letters 4 (3): 139-148 (1996) 1 [ 35 ] 2 [ 29 ] [ 34 ] [ 39 ] 3 [ 16 ] [ 26 ] 4 [ 33 ] [ 36 ] 5 [ 36 ] 6 [ 12 ] 7 [ 17 ] [ 18 ] [ 25 ] 8 [ 39 ] 9 [ 1 ] [ 2 ] [ 3 ] [ 4 ] 10 [ 35 ] 11 [ 27 ] [ 31 ] [ 32 ] [ 35 ] 12 [ 9 ] [ 11 ] [ 15 ] [ 16 ] [ 20 ] [ 23 ] [ 24 ] [ 26 ] [ 28 ] [ 30 ] [ 37 ] 13 [ 41 ] 14 [ 8 ] 15 [ 41 ] 16 [ 18 ] [ 25 ] [ 34 ] 17 [ 29 ] 18 [ 36 ] [ 38 ] [ 40 ] [ 41 ] 19 [ 12 ] [ 13 ] 20 [ 32 ] 21 [ 8 ] 22 [ 35 ] 23 [ 24 ] 24 [ 12 ] 25 [ 10 ] [ 11 ] [ 22 ]  ©2006 Association for Computing Machinery |
