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HAIS
2010
Springer
14 years 1 months ago
Graph-Based Model-Selection Framework for Large Ensembles
The intuition behind ensembles is that different prediciton models compensate each other’s errors if one combines them in an appropriate way. In case of large ensembles a lot of...
Krisztian Buza, Alexandros Nanopoulos, Lars Schmid...
LREC
2008
140views Education» more  LREC 2008»
13 years 10 months ago
Toward Active Learning in Data Selection: Automatic Discovery of Language Features During Elicitation
Data Selection has emerged as a common issue in language technologies. We define Data Selection as the choosing of a subset of training data that is most effective for a given tas...
Jonathan Clark, Robert E. Frederking, Lori S. Levi...
ICCCN
2007
IEEE
13 years 9 months ago
Online Selection of Tracking Features using AdaBoost
In this paper, a novel feature selection algorithm for object tracking is proposed. This algorithm performs more robust than the previous works by taking the correlation between f...
Ying-Jia Yeh, Chiou-Ting Hsu
IJCV
2008
106views more  IJCV 2008»
13 years 9 months ago
A Model-Selection Framework for Multibody Structure-and-Motion of Image Sequences
Given an image sequence of a scene consisting of multiple rigidly moving objects, multi-body structure-and-motion (MSaM) is the task to segment the image feature tracks into the d...
Konrad Schindler, David Suter, Hanzi Wang
MCS
2010
Springer
13 years 7 months ago
A Support Kernel Machine for Supervised Selective Combining of Diverse Pattern-Recognition Modalities
Abstract. The Support Kernel Machine (SKM) and the Relevance Kernel Machine (RKM) are two principles for selectively combining objectrepresentation modalities of different kinds b...
Alexander Tatarchuk, Eugene Urlov, Vadim Mottl, Da...