Classification, Regression, and Feature Selection
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Klaus Obermayer | Sepp Hochreiter | Revised December | S. Hochreiter | K. Obermayer | Revised December
[1] M. Kendall,et al. The advanced theory of statistics , 1945 .
[2] Isabelle Guyon,et al. An Introduction to Variable and Feature Selection , 2003, J. Mach. Learn. Res..
[3] D. Botstein,et al. A gene expression database for the molecular pharmacology of cancer , 2000, Nature Genetics.
[4] Volker Roth,et al. Nonlinear Discriminant Analysis Using Kernel Functions , 1999, NIPS.
[5] Thomas G. Dietterich. Approximate Statistical Tests for Comparing Supervised Classification Learning Algorithms , 1998, Neural Computation.
[6] Jon Kleinberg,et al. Authoritative sources in a hyperlinked environment , 1999, SODA '98.
[7] T. Poggio,et al. Prediction of central nervous system embryonal tumour outcome based on gene expression , 2002, Nature.
[8] G. Baudat,et al. Generalized Discriminant Analysis Using a Kernel Approach , 2000, Neural Computation.
[9] Y. Benjamini,et al. Controlling the false discovery rate: a practical and powerful approach to multiple testing , 1995 .
[10] John Shawe-Taylor,et al. A framework for structural risk minimisation , 1996, COLT '96.
[11] Y. Benjamini,et al. THE CONTROL OF THE FALSE DISCOVERY RATE IN MULTIPLE TESTING UNDER DEPENDENCY , 2001 .
[12] Ronald Rousseau,et al. Requirements for a cocitation similarity measure, with special reference to Pearson's correlation coefficient , 2003, J. Assoc. Inf. Sci. Technol..
[13] Amos Bairoch,et al. The PROSITE database, its status in 2002 , 2002, Nucleic Acids Res..
[14] Yudong D. He,et al. Gene expression profiling predicts clinical outcome of breast cancer , 2002, Nature.
[15] R. Drmanac,et al. Sequencing of megabase plus DNA by hybridization: theory of the method. , 1989, Genomics.
[16] H. Luetkepohl. The Handbook of Matrices , 1996 .
[17] John C. Platt,et al. Fast training of support vector machines using sequential minimal optimization, advances in kernel methods , 1999 .
[18] C. Breneman,et al. Prediction of protein retention in ion-exchange systems using molecular descriptors obtained from crystal structure. , 2001, Analytical chemistry.
[19] D. Lipman,et al. Rapid and sensitive protein similarity searches. , 1985, Science.
[20] John C. Smart,et al. Mapping intellectual structure of a scientific subfield through author cocitations , 1990, J. Am. Soc. Inf. Sci..
[21] Vladimir Vapnik,et al. Statistical learning theory , 1998 .
[22] Klaus Obermayer,et al. Gene Selection for Microarray Data , 2004 .
[23] Vladimir N. Vapnik,et al. The Nature of Statistical Learning Theory , 2000, Statistics for Engineering and Information Science.
[24] R. C. Williamson,et al. Generalization Bounds via Eigenvalues of the Gram matrix , 1999 .
[25] Laurie J. Heyer,et al. Exploring expression data: identification and analysis of coexpressed genes. , 1999, Genome research.
[26] S. Elgin,et al. Nucleosome positioning and gene regulation , 1994, Journal of cellular biochemistry.
[27] Olvi L. Mangasarian,et al. Generalized Support Vector Machines , 1998 .
[28] Andrea Califano,et al. Analysis of Gene Expression Microarrays for Phenotype Classification , 2000, ISMB.
[29] Amos Bairoch,et al. PROSITE: A Documented Database Using Patterns and Profiles as Motif Descriptors , 2002, Briefings Bioinform..
[30] John Shawe-Taylor,et al. Structural Risk Minimization Over Data-Dependent Hierarchies , 1998, IEEE Trans. Inf. Theory.
[31] Wei Chu,et al. Bayesian support vector regression using a unified loss function , 2004, IEEE Transactions on Neural Networks.
[32] C. Blakemore,et al. Analysis of connectivity in the cat cerebral cortex , 1995, The Journal of neuroscience : the official journal of the Society for Neuroscience.
[33] Ron Kohavi,et al. Wrappers for Feature Subset Selection , 1997, Artif. Intell..
[34] Todd,et al. Diffuse large B-cell lymphoma outcome prediction by gene-expression profiling and supervised machine learning , 2002, Nature Medicine.
[35] Pat Langley,et al. Selection of Relevant Features and Examples in Machine Learning , 1997, Artif. Intell..
[36] W. Bains,et al. A novel method for nucleic acid sequence determination. , 1988, Journal of theoretical biology.
[37] Joachim M. Buhmann,et al. Pairwise Data Clustering by Deterministic Annealing , 1997, IEEE Trans. Pattern Anal. Mach. Intell..
[38] Jason Weston,et al. Gene Selection for Cancer Classification using Support Vector Machines , 2002, Machine Learning.
[39] B. Scholkopf,et al. Fisher discriminant analysis with kernels , 1999, Neural Networks for Signal Processing IX: Proceedings of the 1999 IEEE Signal Processing Society Workshop (Cat. No.98TH8468).
[40] Klaus Obermayer,et al. Coulomb Classifiers: Generalizing Support Vector Machines via an Analogy to Electrostatic Systems , 2002, NIPS.
[41] Gunnar Rätsch,et al. Soft Margins for AdaBoost , 2001, Machine Learning.
[42] Klaus Obermayer,et al. Classification on Pairwise Proximity Data , 1998, NIPS.
[43] K. Khrapko,et al. [Determination of the nucleotide sequence of DNA using hybridization with oligonucleotides. A new method]. , 1988, Doklady Akademii nauk SSSR.
[44] Sayan Mukherjee,et al. Feature Selection for SVMs , 2000, NIPS.