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» Relation Extraction Using Support Vector Machine
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KDD
2003
ACM
180views Data Mining» more  KDD 2003»
16 years 3 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
IPPS
2007
IEEE
15 years 9 months ago
On the Power of the Multiple Associative Computing (MASC) Model Related to That of Reconfigurable Bus-Based Models
: The MASC model is a multi-SIMD model that uses control parallelism to coordinate the interaction of data parallel threads. It supports a generalized associative style of parallel...
Mingxian Jin, Johnnie W. Baker
158
Voted
ICMLA
2009
15 years 28 days ago
Knowledge Transfer for Feature Generation in Document Classification
One important problem in machine learning is how to extract knowledge from prior experience, then transfer and apply this knowledge in new learning tasks. To address this problem, ...
Jian Zhang, Shobhit S. Shakya
ALT
2006
Springer
16 years 4 days ago
Learning Linearly Separable Languages
This paper presents a novel paradigm for learning languages that consists of mapping strings to an appropriate high-dimensional feature space and learning a separating hyperplane i...
Leonid Kontorovich, Corinna Cortes, Mehryar Mohri
PR
2006
95views more  PR 2006»
15 years 3 months ago
Classification of acoustic events using SVM-based clustering schemes
Acoustic events produced in controlled environments may carry information useful for perceptually aware interfaces. In this paper we focus on the problem of classifying 16 types o...
Andrey Temko, Climent Nadeu