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KDD
2008
ACM
167views Data Mining» more  KDD 2008»
16 years 7 months ago
A sequential dual method for large scale multi-class linear svms
Efficient training of direct multi-class formulations of linear Support Vector Machines is very useful in applications such as text classification with a huge number examples as w...
S. Sathiya Keerthi, S. Sundararajan, Kai-Wei Chang...
KDD
2008
ACM
128views Data Mining» more  KDD 2008»
16 years 7 months ago
Bypass rates: reducing query abandonment using negative inferences
We introduce a new approach to analyzing click logs by examining both the documents that are clicked and those that are bypassed--documents returned higher in the ordering of the ...
Atish Das Sarma, Sreenivas Gollapudi, Samuel Ieong
KDD
2008
ACM
182views Data Mining» more  KDD 2008»
16 years 7 months ago
Classification with partial labels
In this paper, we address the problem of learning when some cases are fully labeled while other cases are only partially labeled, in the form of partial labels. Partial labels are...
Nam Nguyen, Rich Caruana
KDD
2006
ACM
165views Data Mining» more  KDD 2006»
16 years 7 months ago
Training linear SVMs in linear time
Linear Support Vector Machines (SVMs) have become one of the most prominent machine learning techniques for highdimensional sparse data commonly encountered in applications like t...
Thorsten Joachims
KDD
2005
ACM
166views Data Mining» more  KDD 2005»
16 years 7 months ago
A general model for clustering binary data
Clustering is the problem of identifying the distribution of patterns and intrinsic correlations in large data sets by partitioning the data points into similarity classes. This p...
Tao Li