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ICML
1997
IEEE
16 years 2 months ago
Characterizing the generalization performance of model selection strategies
Abstract: We investigate the structure of model selection problems via the bias/variance decomposition. In particular, we characterize the essential structure of a model selection ...
Dale Schuurmans, Lyle H. Ungar, Dean P. Foster
AAAI
2006
15 years 3 months ago
Learning Basis Functions in Hybrid Domains
Markov decision processes (MDPs) with discrete and continuous state and action components can be solved efficiently by hybrid approximate linear programming (HALP). The main idea ...
Branislav Kveton, Milos Hauskrecht
BTW
2005
Springer
113views Database» more  BTW 2005»
15 years 7 months ago
A Learning Optimizer for a Federated Database Management System
: Optimizers in modern DBMSs utilize a cost model to choose an efficient query execution plan (QEP) among all possible ones for a given query. The accuracy of the cost estimates de...
Stephan Ewen, Michael Ortega-Binderberger, Volker ...
ICML
2004
IEEE
16 years 2 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
GECCO
2003
Springer
160views Optimization» more  GECCO 2003»
15 years 7 months ago
Using Genetic Algorithms for Data Mining Optimization in an Educational Web-Based System
This paper presents an approach for classifying students in order to predict their final grade based on features extracted from logged data in an education web-based system. A comb...
Behrouz Minaei-Bidgoli, William F. Punch