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» Semi-supervised learning by search of optimal target vector
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ISNN
2011
Springer
12 years 11 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
CGO
2005
IEEE
14 years 2 months ago
Optimizing Sorting with Genetic Algorithms
The growing complexity of modern processors has made the generation of highly efficient code increasingly difficult. Manual code generation is very time consuming, but it is oft...
Xiaoming Li, María Jesús Garzar&aacu...
MIR
2004
ACM
171views Multimedia» more  MIR 2004»
14 years 2 months ago
Mean version space: a new active learning method for content-based image retrieval
In content-based image retrieval, relevance feedback has been introduced to narrow the gap between low-level image feature and high-level semantic concept. Furthermore, to speed u...
Jingrui He, Hanghang Tong, Mingjing Li, HongJiang ...
MLG
2007
Springer
14 years 2 months ago
A Universal Kernel for Learning Regular Languages
We give a universal kernel that renders all the regular languages linearly separable. We are not able to compute this kernel efficiently and conjecture that it is intractable, but...
Leonid Kontorovich
ICPR
2010
IEEE
13 years 6 months ago
User Adaptive Clustering for Large Image Databases
Abstract--Searching large image databases is a time consuming process when done manually. Current CBIR methods mostly rely on training data in specific domains. When source and dom...
Mohammad Mehdi Saboorian, Mansour Jamzad, Hamid R....