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ICASSP
2010
IEEE
15 years 4 months ago
Semi-Supervised Fisher Linear Discriminant (SFLD)
Supervised learning uses a training set of labeled examples to compute a classifier which is a mapping from feature vectors to class labels. The success of a learning algorithm i...
Seda Remus, Carlo Tomasi
ICCV
2007
IEEE
15 years 10 months ago
Co-Tracking Using Semi-Supervised Support Vector Machines
This paper treats tracking as a foreground/background classification problem and proposes an online semisupervised learning framework. Initialized with a small number of labeled ...
Feng Tang, Shane Brennan, Qi Zhao, Hai Tao
PR
2008
161views more  PR 2008»
15 years 4 months ago
A study on three linear discriminant analysis based methods in small sample size problem
In this paper, we make a study on three Linear Discriminant Analysis (LDA) based methods: Regularized Discriminant Analysis (RDA), Discriminant Common Vectors (DCV) and Maximal Ma...
Jun Liu, Songcan Chen, Xiaoyang Tan
SDM
2009
SIAM
180views Data Mining» more  SDM 2009»
16 years 1 months ago
Hierarchical Linear Discriminant Analysis for Beamforming.
This paper demonstrates the applicability of the recently proposed supervised dimension reduction, hierarchical linear discriminant analysis (h-LDA) to a well-known spatial locali...
Barry L. Drake, Haesun Park, Jaegul Choo
AAECC
2007
Springer
89views Algorithms» more  AAECC 2007»
15 years 10 months ago
Links Between Discriminating and Identifying Codes in the Binary Hamming Space
Let Fn be the binary n-cube, or binary Hamming space of dimension n, endowed with the Hamming distance, and En (respectively, On ) the set of vectors with even (respectively, odd)...
Irène Charon, Gérard D. Cohen, Olivi...