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» Support Vector Regression Using Mahalanobis Kernels
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JMLR
2010
135views more  JMLR 2010»
13 years 7 months ago
Bundle Methods for Regularized Risk Minimization
A wide variety of machine learning problems can be described as minimizing a regularized risk functional, with different algorithms using different notions of risk and differen...
Choon Hui Teo, S. V. N. Vishwanathan, Alex J. Smol...
ICIP
2001
IEEE
14 years 10 months ago
Higher order autocorrelations for pattern classification
The use of higher-order local autocorrelations as features for pattern recognition has been acknowledged since many years, but their applicability was restricted to relatively low...
Vlad Popovici, Jean-Philippe Thiran
KDD
2003
ACM
180views Data Mining» more  KDD 2003»
14 years 9 months ago
Classifying large data sets using SVMs with hierarchical clusters
Support vector machines (SVMs) have been promising methods for classification and regression analysis because of their solid mathematical foundations which convey several salient ...
Hwanjo Yu, Jiong Yang, Jiawei Han
ICASSP
2010
IEEE
13 years 7 months ago
A comparison of approaches for modeling prosodic features in speaker recognition
Prosodic information has been successfully used for speaker recognition for more than a decade. The best-performing prosodic system to date has been one based on features extracte...
Luciana Ferrer, Nicolas Scheffer, Elizabeth Shribe...
SIGMOD
2010
ACM
324views Database» more  SIGMOD 2010»
14 years 1 months ago
Similarity search and locality sensitive hashing using ternary content addressable memories
Similarity search methods are widely used as kernels in various data mining and machine learning applications including those in computational biology, web search/clustering. Near...
Rajendra Shinde, Ashish Goel, Pankaj Gupta, Debojy...