real or abstract. It provides a widely applicable approach to the prediction of compensatory substitutions for CPDs, avoiding any reliance on rigid non-probabilistic criteria or st...
B. C. Easton, A. V. Isaev, Gavin A. Huttley, Peter...
Constraint Satisfaction Problems (CSPs) are ubiquitous in Artificial Intelligence. The backtrack algorithms that maintain some local consistency during search have become the de ...
IAPR Workshop on Machine Vision and Applications, pp. 455-458, 2000, Tokyo, Japan In this paper, we integrate the model-based tracking and local contexture (temporal and spatial) ...
We present a novel boosting algorithm, called SoftBoost, designed for sets of binary labeled examples that are not necessarily separable by convex combinations of base hypotheses....
Manfred K. Warmuth, Karen A. Glocer, Gunnar Rä...
Abstract. In constraint satisfaction, local search is an incomplete method for finding a solution to a problem. Solving a general constraint satisfaction problem (CSP) is known to...
Montserrat Abril, Miguel A. Salido, Federico Barbe...