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» Learning Abstraction Hierarchies for Problem Solving
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ECML
2006
Springer
14 years 10 days ago
Approximate Policy Iteration for Closed-Loop Learning of Visual Tasks
Abstract. Approximate Policy Iteration (API) is a reinforcement learning paradigm that is able to solve high-dimensional, continuous control problems. We propose to exploit API for...
Sébastien Jodogne, Cyril Briquet, Justus H....
ECAI
2006
Springer
14 years 10 days ago
Automatic Generation of Implied Constraints
Abstract. A well-known difficulty with solving Constraint Satisfaction Problems (CSPs) is that, while one formulation of a CSP may enable a solver to solve it quickly, a different ...
John Charnley, Simon Colton, Ian Miguel
CP
2007
Springer
14 years 2 months ago
On Universal Restart Strategies for Backtracking Search
Abstract. Constraint satisfaction and propositional satisfiability problems are often solved using backtracking search. Previous studies have shown that a technique called randomi...
Huayue Wu, Peter van Beek
ICMLA
2010
13 years 6 months ago
An All-at-once Unimodal SVM Approach for Ordinal Classification
Abstract--Support vector machines (SVMs) were initially proposed to solve problems with two classes. Despite the myriad of schemes for multiclassification with SVMs proposed since ...
Joaquim F. Pinto da Costa, Ricardo Sousa, Jaime S....
PKDD
2009
Springer
117views Data Mining» more  PKDD 2009»
14 years 3 months ago
New Regularized Algorithms for Transductive Learning
Abstract. We propose a new graph-based label propagation algorithm for transductive learning. Each example is associated with a vertex in an undirected graph and a weighted edge be...
Partha Pratim Talukdar, Koby Crammer