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ML
2002
ACM
127views Machine Learning» more  ML 2002»
13 years 9 months ago
Sparse Regression Ensembles in Infinite and Finite Hypothesis Spaces
We examine methods for constructing regression ensembles based on a linear program (LP). The ensemble regression function consists of linear combinations of base hypotheses generat...
Gunnar Rätsch, Ayhan Demiriz, Kristin P. Benn...
ML
2002
ACM
123views Machine Learning» more  ML 2002»
13 years 9 months ago
Feature Generation Using General Constructor Functions
Most classification algorithms receive as input a set of attributes of the classified objects. In many cases, however, the supplied set of attributes is not sufficient for creatin...
Shaul Markovitch, Dan Rosenstein
ML
2002
ACM
154views Machine Learning» more  ML 2002»
13 years 9 months ago
Technical Update: Least-Squares Temporal Difference Learning
TD() is a popular family of algorithms for approximate policy evaluation in large MDPs. TD() works by incrementally updating the value function after each observed transition. It h...
Justin A. Boyan
JSC
1998
68views more  JSC 1998»
13 years 9 months ago
An Algorithm for Computing the Integral Closure
We present an algorithm for computing the integral closure of a reduced ring that is finitely generated over a finite field. Leonard and Pellikaan [4] devised an algorithm for c...
Theo De Jong
MCS
2002
Springer
13 years 9 months ago
Forward and Backward Selection in Regression Hybrid Network
Abstract. We introduce a Forward Backward and Model Selection algorithm (FBMS) for constructing a hybrid regression network of radial and perceptron hidden units. The algorithm det...
Shimon Cohen, Nathan Intrator
KI
2002
Springer
13 years 9 months ago
Incremental Fuzzy Decision Trees
Abstract. We present a new classification algorithm that combines three properties: It generates decision trees, which proved a valuable and intelligible tool for classification an...
Marina Guetova, Steffen Hölldobler, Hans-Pete...
JEA
1998
133views more  JEA 1998»
13 years 9 months ago
A New Deterministic Parallel Sorting Algorithm with an Experimental Evaluation
We introduce a new deterministic parallel sorting algorithm based on the regular sampling approach. The algorithm uses only two rounds of regular all-to-all personalized communica...
David R. Helman, Joseph JáJá, David ...
JMLR
2002
83views more  JMLR 2002»
13 years 9 months ago
On Online Learning of Decision Lists
A fundamental open problem in computational learning theory is whether there is an attribute efficient learning algorithm for the concept class of decision lists (Rivest, 1987; Bl...
Ziv Nevo, Ran El-Yaniv
JMLR
2002
140views more  JMLR 2002»
13 years 9 months ago
On Boosting with Polynomially Bounded Distributions
We construct a framework which allows an algorithm to turn the distributions produced by some boosting algorithms into polynomially smooth distributions (w.r.t. the PAC oracle...
Nader H. Bshouty, Dmitry Gavinsky
JMIV
2002
72views more  JMIV 2002»
13 years 9 months ago
Estimating Overcomplete Independent Component Bases for Image Windows
Estimating overcomplete ICA bases for image windows is a difficult problem. Most algorithms require the estimation of values of the independent components which leads to computatio...
Aapo Hyvärinen, Mika Inki