Sciweavers

11 search results - page 1 / 3
» Descent Methods for Tuning Parameter Refinement
Sort
View
JMLR
2010
88views more  JMLR 2010»
13 years 2 months ago
Descent Methods for Tuning Parameter Refinement
This paper addresses multidimensional tuning parameter selection in the context of "train-validate-test" and K-fold cross validation. A coarse grid search over tuning pa...
Alexander Lorbert, Peter J. Ramadge
ISNN
2005
Springer
14 years 25 days ago
Multiple Parameter Selection for LS-SVM Using Smooth Leave-One-Out Error
In least squares support vector (LS-SVM), the key challenge lies in the selection of free parameters such as kernel parameters and tradeoff parameter. However, when a large number ...
Liefeng Bo, Ling Wang, Licheng Jiao
ML
2002
ACM
121views Machine Learning» more  ML 2002»
13 years 7 months ago
Choosing Multiple Parameters for Support Vector Machines
The problem of automatically tuning multiple parameters for pattern recognition Support Vector Machines (SVMs) is considered. This is done by minimizing some estimates of the gener...
Olivier Chapelle, Vladimir Vapnik, Olivier Bousque...
FORMATS
2007
Springer
13 years 11 months ago
Combining Formal Verification with Observed System Execution Behavior to Tune System Parameters
Resource limited DRE (Distributed Real-time Embedded) systems can benefit greatly from dynamic adaptation of system parameters. We propose a novel approach that employs iterative t...
Minyoung Kim, Mark-Oliver Stehr, Carolyn L. Talcot...
ICMCS
2006
IEEE
124views Multimedia» more  ICMCS 2006»
14 years 1 months ago
Exploring Automatic Query Refinement for Text-Based Video Retrieval
Text-based search using video speech transcripts is a popular approach for granular video retrieval at the shot or story level. However, misalignment of speech and visual tracks, ...
Timo Volkmer, Apostol Natsev