6095 search results - page 126 / 1219 » Learning in Local Search |
SCALESPACE
2009
Springer
14 years 3 months ago
2009
Springer
Abstract. Segmentation of images is often posed as a variational problem. As such, it is solved by formulating an energy functional depending on a contour and other image derived t...
AAAI
1996
13 years 10 months ago
1996
Learning during backtrack search is a space-intensive process that records information (such as additional constraints) in order to avoid redundant work. In this paper, we analyze...
UAI
1996
13 years 10 months ago
1996
In this paper we examine a novel addition to the known methods for learning Bayesian networks from data that improves the quality of the learned networks. Our approach explicitly ...
COLT
2008
Springer
13 years 10 months ago
2008
Springer
We consider the question of why modern machine learning methods like support vector machines outperform earlier nonparametric techniques like kNN. Our approach investigates the lo...
ICANN
2005
Springer
14 years 2 months ago
2005
Springer
Abstract. Tuning hyper-parameters is a necessary step to improve learning algorithm performances. For Support Vector Machine classifiers, adjusting kernel parameters increases dra...