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ICANN
2001
Springer
14 years 9 days ago
Feature Extraction Using ICA
In manipulating data such as in supervised learning, we often extract new features from original features for the purpose of reducing the dimensions of feature space and achieving ...
Nojun Kwak, Chong-Ho Choi, Jin-Young Choi
ICPR
2010
IEEE
13 years 8 months ago
High-Level Feature Extraction Using SIFT GMMs and Audio Models
—We propose a statistical framework for high-level feature extraction that uses SIFT Gaussian mixture models (GMMs) and audio models. SIFT features were extracted from all the im...
Nakamasa Inoue, Tatsuhiko Saito, Koichi Shinoda, S...
IR
2010
13 years 6 months ago
LETOR: A benchmark collection for research on learning to rank for information retrieval
LETOR is a benchmark collection for the research on learning to rank for information retrieval, released by Microsoft Research Asia. In this paper, we describe the details of the L...
Tao Qin, Tie-Yan Liu, Jun Xu, Hang Li
ICML
2006
IEEE
14 years 8 months ago
Active sampling for detecting irrelevant features
The general approach for automatically driving data collection using information from previously acquired data is called active learning. Traditional active learning addresses the...
Sriharsha Veeramachaneni, Emanuele Olivetti, Paolo...
CICLING
2006
Springer
13 years 11 months ago
Verb Sense Disambiguation Using Support Vector Machines: Impact of WordNet-Extracted Features
The disambiguation of verbs is usually considered to be more difficult with respect to other part-of-speech categories. This is due both to the high polysemy of verbs compared with...
Davide Buscaldi, Paolo Rosso, Ferran Pla, Encarna ...