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» Machine Learning by Function Decomposition
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NIPS
2008
15 years 1 months ago
QUIC-SVD: Fast SVD Using Cosine Trees
The Singular Value Decomposition is a key operation in many machine learning methods. Its computational cost, however, makes it unscalable and impractical for applications involvi...
Michael P. Holmes, Alexander G. Gray, Charles Lee ...
GECCO
2005
Springer
136views Optimization» more  GECCO 2005»
15 years 5 months ago
Preventing overfitting in GP with canary functions
Overfitting is a fundamental problem of most machine learning techniques, including genetic programming (GP). Canary functions have been introduced in the literature as a concept ...
Nate Foreman, Matthew P. Evett
LREC
2008
141views Education» more  LREC 2008»
15 years 1 months ago
Creating Glossaries Using Pattern-Based and Machine Learning Techniques
One of the aims of the Language Technology for eLearning project is to show that Natural Language Processing techniques can be employed to enhance the learning process. To this en...
Eline Westerhout, Paola Monachesi
JMLR
2002
89views more  JMLR 2002»
14 years 11 months ago
The Set Covering Machine
We extend the classical algorithms of Valiant and Haussler for learning compact conjunctions and disjunctions of Boolean attributes to allow features that are constructed from the...
Mario Marchand, John Shawe-Taylor
ICML
2001
IEEE
16 years 18 days ago
A Unified Loss Function in Bayesian Framework for Support Vector Regression
In this paper, we propose a unified non-quadratic loss function for regression known as soft insensitive loss function (SILF). SILF is a flexible model and possesses most of the d...
Wei Chu, S. Sathiya Keerthi, Chong Jin Ong