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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
140views Data Mining» more  KDD 2008»
16 years 7 months ago
On updates that constrain the features' connections during learning
In many multiclass learning scenarios, the number of classes is relatively large (thousands,...), or the space and time efficiency of the learning system can be crucial. We invest...
Omid Madani, Jian Huang 0002
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
2006
ACM
172views Data Mining» more  KDD 2006»
16 years 7 months ago
Attack detection in time series for recommender systems
Recent research has identified significant vulnerabilities in recommender systems. Shilling attacks, in which attackers introduce biased ratings in order to influence future recom...
Sheng Zhang, Amit Chakrabarti, James Ford, Fillia ...
KDD
2005
ACM
104views Data Mining» more  KDD 2005»
16 years 7 months ago
Mining tree queries in a graph
We present an algorithm for mining tree-shaped patterns in a large graph. Novel about our class of patterns is that they can contain constants, and can contain existential nodes w...
Bart Goethals, Eveline Hoekx, Jan Van den Bussche