312 search results - page 51 / 63 » Combined Optimization of Feature Selection and Algorithm Par... |
ML
1998
ACM
13 years 8 months ago
1998
ACM
We introduce, analyze and demonstrate a recursive hierarchical generalization of the widely used hidden Markov models, which we name Hierarchical Hidden Markov Models (HHMM). Our m...
NLPRS
2001
Springer
14 years 1 months ago
2001
Springer
Recent research in automated learning has focused on algorithms that learn from a combination of tagged and untagged data. Such algorithms can be referred to as semi-supervised in...
CIDM
2007
IEEE
14 years 22 days ago
2007
IEEE
Kernel methods are effective approaches to the modeling of structured objects in learning algorithms. Their major drawback is the typically high computational complexity of kernel ...
ICANN
2005
Springer
14 years 2 months ago
2005
Springer
One aim of Meta-learning techniques is to minimize the time needed for problem solving, and the effort of parameter hand-tuning, by automating algorithm selection. The predictive m...
CIVR
2010
Springer
14 years 1 months ago
2010
Springer
This paper describes an approach to optimize query by visual example results, by combining visual features and implicit user feedback in interactive video retrieval. To this end, ...