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» The Shortcut Problem - Complexity and Approximation
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GECCO
2007
Springer
192views Optimization» more  GECCO 2007»
15 years 10 months ago
Convergence of stochastic search algorithms to gap-free pareto front approximations
Recently, a convergence proof of stochastic search algorithms toward finite size Pareto set approximations of continuous multi-objective optimization problems has been given. The...
Oliver Schütze, Marco Laumanns, Emilia Tantar...
GECCO
2006
Springer
177views Optimization» more  GECCO 2006»
15 years 7 months ago
Hyper-ellipsoidal conditions in XCS: rotation, linear approximation, and solution structure
The learning classifier system XCS is an iterative rulelearning system that evolves rule structures based on gradient-based prediction and rule quality estimates. Besides classifi...
Martin V. Butz, Pier Luca Lanzi, Stewart W. Wilson
CORR
2010
Springer
170views Education» more  CORR 2010»
15 years 3 months ago
Global Optimization for Value Function Approximation
Existing value function approximation methods have been successfully used in many applications, but they often lack useful a priori error bounds. We propose a new approximate bili...
Marek Petrik, Shlomo Zilberstein
119
Voted
CORR
2010
Springer
130views Education» more  CORR 2010»
15 years 3 months ago
Approximated Structured Prediction for Learning Large Scale Graphical Models
In this paper we propose an approximated structured prediction framework for large scale graphical models and derive message-passing algorithms for learning their parameters effic...
Tamir Hazan, Raquel Urtasun
ALT
2000
Springer
16 years 23 days ago
On Approximate Learning by Multi-layered Feedforward Circuits
Abstract. We consider the problem of efficient approximate learning by multilayered feedforward circuits subject to two objective functions. First, we consider the objective to ma...
Bhaskar DasGupta, Barbara Hammer