Deterministic and statistical methods in machine learning
Permalink: | http://skupni.nsk.hr/Record/fer.KOHA-OAI-FER:34765/TOC |
---|---|
Ostali autori: | Sheffield Machine Learning Workshop (-) |
Ostali autori: | Winkler, Joab (-), Niranjan, Mahesan, Lawrence, Neil (Neil D.) |
Vrsta građe: | Knjiga |
Jezik: | eng |
Impresum: |
Berlin ; New York :
Springer,
c2005.
|
Nakladnička cjelina: |
Lecture notes in computer science ;
3635. Lecture notes in computer science. Lecture notes in artificial intelligence. |
Predmet: | |
Online pristup: |
Restricted to SpringerLink subscribers Publisher description |
Sadržaj:
- Object Recognition via Local Patch Labelling
- - Christopher M. Bishop, Ilkay Ulusoy
- Multi Channel Sequence Processing
- - Samy Bengio, Hervé Bourlard
- Bayesian Kernel Learning Methods for Parametric Accelerated Life Survival Analysis
- - Gavin C. Cawley, Nicola L. C. Talbot, Gareth J. Janacek, Michael W. Peck
- Extensions of the Informative Vector Machine
- - Neil D. Lawrence, John C. Platt, Michael I. Jordan
- Efficient Communication by Breathing
- - Tom H. Shorrock, David J. C. MacKay, Chris J. Ball
- Guiding Local Regression Using Visualisation
- - Dharmesh M. Maniyar, Ian T. Nabney
- Transformations of Gaussian Process Priors
- - Roderick Murray-Smith, Barak A. Pearlmutter
- Kernel Based Learning Methods: Regularization Networks and RBF Networks
- - Petra Kudová, Roman Neruda
- Redundant Bit Vectors for Quickly Searching High-Dimensional Regions
- - Jonathan Goldstein, John C. Plat, Christopher J. C. Burges
- Bayesian Independent Component Analysis with Prior Constraints: An Application in Biosignal Analysis
- - Stephen Roberts, Rizwan Choudrey
- Ensemble Algorithms for Feature Selection
- - Jeremy D. Rogers, Steve R. Gunn
- Can Gaussian Process Regression Be Made Robust Against Model Mismatch?
- - Peter Sollich
- Understanding Gaussian Process Regression Using the Equivalent Kernel
- - Peter Sollich, Christopher K. I. Williams
- Integrating Binding Site Predictions Using Non-linear Classification Methods
- - Yi Sun, Mark Robinson, Rod Adams, Paul Kaye, Alistair Rust, Neil Davey
- Support Vector Machine to Synthesise Kernels
- - Hongying Meng, John Shawe-Taylor, Sandor Szedmak, Jason D. R. Farquhar
- Appropriate Kernel Functions for Support Vector Machine Learning with Sequences of Symbolic Data
- - Bram Vanschoenwinkel, Bernard Manderick
- Variational Bayes Estimation of Mixing Coefficients
- - Bo Wang, D. M. Titterington
- A Comparison of Condition Numbers for the Full Rank Least Squares Problem
- - Joab R. Winkler
- SVM Based Learning System for Information Extraction
- - Yaoyong Li, Kalina Bontcheva, Hamish Cunningham