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PRL
2008
133views more  PRL 2008»
15 years 3 months ago
Better multiclass classification via a margin-optimized single binary problem
We develop a new multiclass classification method that reduces the multiclass problem to a single binary classifier (SBC). Our method constructs the binary problem by embedding sm...
Ran El-Yaniv, Dmitry Pechyony, Elad Yom-Tov
JMLR
2002
135views more  JMLR 2002»
15 years 2 months ago
Covering Number Bounds of Certain Regularized Linear Function Classes
Recently, sample complexity bounds have been derived for problems involving linear functions such as neural networks and support vector machines. In many of these theoretical stud...
Tong Zhang
128
Voted
JIIS
2006
73views more  JIIS 2006»
15 years 3 months ago
Using KCCA for Japanese-English cross-language information retrieval and document classification
Kernel Canonical Correlation Analysis (KCCA) is a method of correlating linear relationship between two variables in a kernel defined feature space. A machine learning algorithm b...
Yaoyong Li, John Shawe-Taylor
WWW
2011
ACM
14 years 10 months ago
Parallel boosted regression trees for web search ranking
Gradient Boosted Regression Trees (GBRT) are the current state-of-the-art learning paradigm for machine learned websearch ranking — a domain notorious for very large data sets. ...
Stephen Tyree, Kilian Q. Weinberger, Kunal Agrawal...
ICML
2009
IEEE
16 years 4 months ago
MedLDA: maximum margin supervised topic models for regression and classification
Supervised topic models utilize document's side information for discovering predictive low dimensional representations of documents; and existing models apply likelihoodbased...
Jun Zhu, Amr Ahmed, Eric P. Xing