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PKDD
2009
Springer
118views Data Mining» more  PKDD 2009»
13 years 11 months ago
Sparse Kernel SVMs via Cutting-Plane Training
We explore an algorithm for training SVMs with Kernels that can represent the learned rule using arbitrary basis vectors, not just the support vectors (SVs) from the training set. ...
Thorsten Joachims, Chun-Nam John Yu
SDM
2009
SIAM
119views Data Mining» more  SDM 2009»
14 years 2 months ago
Twin Vector Machines for Online Learning on a Budget.
This paper proposes Twin Vector Machine (TVM), a constant space and sublinear time Support Vector Machine (SVM) algorithm for online learning. TVM achieves its favorable scaling b...
Zhuang Wang, Slobodan Vucetic
KDD
2009
ACM
164views Data Mining» more  KDD 2009»
14 years 5 months ago
Social influence analysis in large-scale networks
In large social networks, nodes (users, entities) are influenced by others for various reasons. For example, the colleagues have strong influence on one's work, while the fri...
Jie Tang, Jimeng Sun, Chi Wang, Zi Yang
WSDM
2010
ACM
204views Data Mining» more  WSDM 2010»
13 years 11 months ago
Learning URL patterns for webpage de-duplication
Presence of duplicate documents in the World Wide Web adversely affects crawling, indexing and relevance, which are the core building blocks of web search. In this paper, we pres...
Hema Swetha Koppula, Krishna P. Leela, Amit Agarwa...
KDD
2009
ACM
158views Data Mining» more  KDD 2009»
14 years 5 months ago
Feature shaping for linear SVM classifiers
: ? Feature Shaping for Linear SVM Classifiers George Forman, Martin Scholz, Shyamsundar Rajaram HP Laboratories HPL-2009-31R1 text classification machine learning, feature weighti...
George Forman, Martin Scholz, Shyamsundar Rajaram