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» Spectral Algorithms for Supervised Learning
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TIP
2008
175views more  TIP 2008»
14 years 9 months ago
Customizing Kernel Functions for SVM-Based Hyperspectral Image Classification
Previous research applying kernel methods such as support vector machines (SVMs) to hyperspectral image classification has achieved performance competitive with the best available ...
Baofeng Guo, Steve R. Gunn, Robert I. Damper, Jame...
ICML
2009
IEEE
15 years 10 months ago
Monte-Carlo simulation balancing
In this paper we introduce the first algorithms for efficiently learning a simulation policy for Monte-Carlo search. Our main idea is to optimise the balance of a simulation polic...
David Silver, Gerald Tesauro
COCOON
2005
Springer
15 years 3 months ago
A Quadratic Lower Bound for Rocchio's Similarity-Based Relevance Feedback Algorithm
Rocchio’s similarity-based relevance feedback algorithm, one of the most important query reformation methods in information retrieval, is essentially an adaptive supervised lear...
Zhixiang Chen, Bin Fu
CC
2006
Springer
124views System Software» more  CC 2006»
15 years 1 months ago
Hybrid Optimizations: Which Optimization Algorithm to Use?
We introduce a new class of compiler heuristics: hybrid optimizations. Hybrid optimizations choose dynamically at compile time which optimization algorithm to apply from a set of d...
John Cavazos, J. Eliot B. Moss, Michael F. P. O'Bo...
ICML
2004
IEEE
15 years 10 months ago
Margin based feature selection - theory and algorithms
Feature selection is the task of choosing a small set out of a given set of features that capture the relevant properties of the data. In the context of supervised classification ...
Ran Gilad-Bachrach, Amir Navot, Naftali Tishby