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» Training Linear Discriminant Analysis in Linear Time
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CVPR
2010
IEEE
15 years 2 months ago
Bayes Optimal Kernel Discriminant Analysis
Kernel methods provide an efficient mechanism to derive nonlinear algorithms. In classification problems as well as in feature extraction, kernel-based approaches map the original...
Di You, Aleix Martinez
VTC
2006
IEEE
174views Communications» more  VTC 2006»
15 years 3 months ago
ML Detection with Blind Linear Prediction for Differential Space-Time Block Code Systems
Abstract— This paper proposes a maximum likelihood detection (MLD) method for the differential space-time block code (DSTBC) in cooperation with blind linear prediction (BLP) of ...
Seree Wanichpakdeedecha, Kazuhiko Fukawa, Hiroshi ...
ICMLA
2008
14 years 11 months ago
A Bayesian Approach to Switching Linear Gaussian State-Space Models for Unsupervised Time-Series Segmentation
Time-series segmentation in the fully unsupervised scenario in which the number of segment-types is a priori unknown is a fundamental problem in many applications. We propose a Ba...
Silvia Chiappa
IBPRIA
2003
Springer
15 years 2 months ago
Hash-Like Fractal Image Compression with Linear Execution Time
The main computational cost in Fractal Image Analysis (FIC) comes from the required range-domain full block comparisons. In this work we propose a new algorithm for this comparison...
Kostadin Koroutchev, José R. Dorronsoro
ISCAS
2006
IEEE
154views Hardware» more  ISCAS 2006»
15 years 3 months ago
A novel Fisher discriminant for biometrics recognition: 2DPCA plus 2DFLD
— this paper presents a novel image feature extraction and recognition method two dimensional linear discriminant analysis (2DLDA) in a much smaller subspace. Image representatio...
R. M. Mutelo, Li Chin Khor, Wai Lok Woo, Satnam Si...