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GECCO
2007
Springer
187views Optimization» more  GECCO 2007»
16 years 15 days ago
Defining implicit objective functions for design problems
In many design tasks it is difficult to explicitly define an objective function. This paper uses machine learning to derive an objective in a feature space based on selected examp...
Sean Hanna
CLIN
2001
15 years 7 months ago
Multi-feature Error Detection in Spoken Dialogue Systems
The present paper evaluates the role selected features and feature combinations play for error detection in spoken dialogue systems. We investigate the relevance of various, readi...
Piroska Lendvai, Antal van den Bosch, Emiel Krahme...
ISNN
2011
Springer
14 years 9 months ago
Orthogonal Feature Learning for Time Series Clustering
This paper presents a new method that uses orthogonalized features for time series clustering and classification. To cluster or classify time series data, either original data or...
Xiaozhe Wang, Leo Lopes
CVPR
2010
IEEE
15 years 11 months ago
The Automatic Design of Feature Spaces for Local Image Descriptors using an Ensemble of Non-linear Feature Extractors
The design of feature spaces for local image descriptors is an important research subject in computer vision due to its applicability in several problems, such as visual classifi...
Gustavo Carneiro
KDD
2007
ACM
154views Data Mining» more  KDD 2007»
16 years 6 months ago
Canonicalization of database records using adaptive similarity measures
It is becoming increasingly common to construct databases from information automatically culled from many heterogeneous sources. For example, a research publication database can b...
Aron Culotta, Michael L. Wick, Robert Hall, Matthe...