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» Learning of Boolean Functions Using Support Vector Machines
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IJCNN
2006
IEEE
14 years 3 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
DSS
2008
186views more  DSS 2008»
13 years 9 months ago
A machine learning approach to web page filtering using content and structure analysis
As the Web continues to grow, it has become increasingly difficult to search for relevant information using traditional search engines. Topic-specific search engines provide an al...
Michael Chau, Hsinchun Chen
ICML
2008
IEEE
14 years 9 months ago
Robust matching and recognition using context-dependent kernels
The success of kernel methods including support vector machines (SVMs) strongly depends on the design of appropriate kernels. While initially kernels were designed in order to han...
Hichem Sahbi, Jean-Yves Audibert, Jaonary Rabariso...
ICIP
2006
IEEE
14 years 10 months ago
Knowledge-Based Supervised Learning Methods in a Classical Problem of Video Object Tracking
In this paper we present a new scheme for detection and tracking of specific objects in a knowledge-based framework. The scheme uses a supervised learning method: Support Vector M...
Lionel Carminati, Jenny Benois-Pineau, Christian J...
COLT
2006
Springer
14 years 22 days ago
Active Sampling for Multiple Output Identification
We study functions with multiple output values, and use active sampling to identify an example for each of the possible output values. Our results for this setting include: (1) Eff...
Shai Fine, Yishay Mansour