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» Approximating Component Selection
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UAI
2004
15 years 4 months ago
Active Model Selection
Classical learning assumes the learner is given a labeled data sample, from which it learns a model. The field of Active Learning deals with the situation where the learner begins...
Omid Madani, Daniel J. Lizotte, Russell Greiner
EOR
2006
148views more  EOR 2006»
15 years 3 months ago
Pareto ant colony optimization with ILP preprocessing in multiobjective project portfolio selection
One of the most important, common and critical management issues lies in determining the "best" project portfolio out of a given set of investment proposals. As this dec...
Karl F. Doerner, Walter J. Gutjahr, Richard F. Har...
TSP
2010
14 years 9 months ago
Low complexity equalization for doubly selective channels modeled by a basis expansion
We propose a novel equalization method for doubly selective wireless channels, whose taps are represented by an arbitrary Basis Expansion Model (BEM). We view such a channel in the...
Tomasz Hrycak, Saptarshi Das, Gerald Matz, Hans G....
PE
2010
Springer
124views Optimization» more  PE 2010»
14 years 10 months ago
High-level approach to modeling of observed system behavior
Current computer systems and communication networks tend to be highly complex, and they typically hide their internal structure from their users. Thus, for selected aspects of cap...
Thomas Begin, Alexandre Brandwajn, Bruno Baynat, B...
GAMEON
2001
15 years 4 months ago
A Learning Architecture for the Game of Go
In this paper, a three-component architecture of a learning environment for Go is sketched, which can be applied to any two-player, deterministic, full information, partizan, comb...
A. B. Meijer