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Note: Links lead to the DBLP on the Web. Michael E. Tipping Hugo Zaragoza , Djoerd Hiemstra , Michael E. Tipping: Bayesian extension to the language model for ad hoc information retrieval. SIGIR 2003 : 4-9 Anita C. Faul , Michael E. Tipping: A Variational Approach to Robust Regression. ICANN 2001 : 95-102 A. C. Faul , Michael E. Tipping: Analysis of Sparse Bayesian Learning. NIPS 2001 : 383-389 Michael E. Tipping: Sparse Bayesian Learning and the Relevance Vector Machine. Journal of Machine Learning Research 1 : 211-244 (2001) Michael E. Tipping: Sparse Kernel Principal Component Analysis. NIPS 2000 : 633-639 Christopher M. Bishop , Michael E. Tipping: Variational Relevance Vector Machines. UAI 2000 : 46-53 Michael E. Tipping: The Relevance Vector Machine. NIPS 1999 : 652-658 Michael E. Tipping, Christopher M. Bishop : Mixtures of Probabilistic Principal Component Analysers. Neural Computation 11 (2): 443-482 (1999) Michael E. Tipping: Probabilistic Visualisation of High-Dimensional Binary Data. NIPS 1998 : 592-598 Christopher M. Bishop , Michael E. Tipping: A Hierarchical Latent Variable Model for Data Visualization. IEEE Transactions on Pattern Analysis and Machine Intelligence 20 (3): 281-293 (1998) Michael E. Tipping, David Lowe : Shadow targets: A novel algorithm for topographic projections by radial basis functions. Neurocomputing 19 (1-3): 211-222 (1998) David Lowe , Michael E. Tipping: NeuroScale: Novel Topographic Feature Extraction using RBF Networks. NIPS 1996 : 543-549 David Lowe , Michael E. Tipping: Feed-Forward Neural Networks and Topographic Mappings for Exploratory Data Analysis. Neural Computing and Applications 4 (2): 83-95 (1996) 1 [ 4 ] [ 6 ] [ 8 ] 2 [ 11 ] 3 [ 12 ] 4 [ 13 ] 5 [ 1 ] [ 2 ] [ 3 ] 6 [ 13 ]  ©2004 Association for Computing Machinery |
