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» Optimization on Support Vector Machines
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69
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ICIAR
2004
Springer
15 years 3 months ago
Learning an Information Theoretic Transform for Object Detection
We present an information theoretic approach for learning a linear dimension reduction transform for object classification. The theoretic guidance of the approach is that the trans...
Jianzhong Fang, Guoping Qiu
63
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TSP
2008
135views more  TSP 2008»
14 years 10 months ago
Nonlinear Channel Equalization With Gaussian Processes for Regression
We propose Gaussian processes for regression as a novel nonlinear equalizer for digital communications receivers. GPR's main advantage, compared to previous nonlinear estimat...
Fernando Pérez-Cruz, Juan José Muril...
91
Voted
PAMI
2010
132views more  PAMI 2010»
14 years 8 months ago
Maximum Likelihood Model Selection for 1-Norm Soft Margin SVMs with Multiple Parameters
—Adapting the hyperparameters of support vector machines (SVMs) is a challenging model selection problem, especially when flexible kernels are to be adapted and data are scarce....
Tobias Glasmachers, Christian Igel
ICMCS
2008
IEEE
181views Multimedia» more  ICMCS 2008»
15 years 4 months ago
Coarse-to-fine video text detection
In this paper, we propose an effective coarse-to-fine algorithm to detect text in video. Firstly, in coarse-detection section, stroke filter is employed to detect all candidate st...
Guangyi Miao, Qingming Huang, Shuqiang Jiang, Wen ...
IJCNN
2006
IEEE
15 years 4 months ago
Learning to Rank by Maximizing AUC with Linear Programming
— Area Under the ROC Curve (AUC) is often used to evaluate ranking performance in binary classification problems. Several researchers have approached AUC optimization by approxi...
Kaan Ataman, W. Nick Street, Yi Zhang