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» On the monotonization of the training set
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124
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JMLR
2010
161views more  JMLR 2010»
14 years 7 months ago
Training and Testing Low-degree Polynomial Data Mappings via Linear SVM
Kernel techniques have long been used in SVM to handle linearly inseparable problems by transforming data to a high dimensional space, but training and testing large data sets is ...
Yin-Wen Chang, Cho-Jui Hsieh, Kai-Wei Chang, Micha...
AIPRF
2007
15 years 2 months ago
Evaluation of Different Approaches to Training a Genre Classifier
This paper presents experiments on classifying web pages by genre. Firstly, a corpus of 1539 manually labeled web pages was prepared. Secondly, 502 genre features were selected ba...
Vedrana Vidulin, Mitja Lustrek, Matjaz Gams
SODA
2008
ACM
104views Algorithms» more  SODA 2008»
15 years 2 months ago
Ranged hash functions and the price of churn
Ranged hash functions generalize hash tables to the setting where hash buckets may come and go over time, a typical case in distributed settings where hash buckets may correspond ...
James Aspnes, Muli Safra, Yitong Yin
PKDD
2009
Springer
118views Data Mining» more  PKDD 2009»
15 years 7 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
93
Voted
ICPR
2008
IEEE
15 years 7 months ago
A fast revised simplex method for SVM training
Active set methods for training the Support Vector Machines (SVM) are advantageous since they enable incremental training and, as we show in this research, do not exhibit exponent...
Christopher Sentelle, Georgios C. Anagnostopoulos,...