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JMLR
2002
138views more  JMLR 2002»
10 years 2 months ago
Text Chunking based on a Generalization of Winnow
This paper describes a text chunking system based on a generalization of the Winnow algorithm. We propose a general statistical model for text chunking which we then convert into ...
Tong Zhang, Fred Damerau, David Johnson
NIPS
2001
10 years 3 months ago
Efficiency versus Convergence of Boolean Kernels for On-Line Learning Algorithms
The paper studies machine learning problems where each example is described using a set of Boolean features and where hypotheses are represented by linear threshold elements. One ...
Roni Khardon, Dan Roth, Rocco A. Servedio
ACL
2001
10 years 4 months ago
Text Chunking using Regularized Winnow
Many machine learning methods have recently been applied to natural language processing tasks. Among them, the Winnow algorithm has been argued to be particularly suitable for NLP...
Tong Zhang, Fred Damerau, David Johnson
ECAI
2008
Springer
10 years 4 months ago
Online Rule Learning via Weighted Model Counting
Online multiplicative weight-update learning algorithms, such as Winnow, have proven to behave remarkably for learning simple disjunctions with few relevant attributes. The aim of ...
Frédéric Koriche
PKDD
2004
Springer
168views Data Mining» more  PKDD 2004»
10 years 8 months ago
Combining Winnow and Orthogonal Sparse Bigrams for Incremental Spam Filtering
Spam filtering is a text categorization task that has attracted significant attention due to the increasingly huge amounts of junk email on the Internet. While current best-pract...
Christian Siefkes, Fidelis Assis, Shalendra Chhabr...
KDD
2004
ACM
126views Data Mining» more  KDD 2004»
11 years 3 months ago
Selection, combination, and evaluation of effective software sensors for detecting abnormal computer usage
We present and empirically analyze a machine-learning approach for detecting intrusions on individual computers. Our Winnowbased algorithm continually monitors user and system beh...
Jude W. Shavlik, Mark Shavlik
KDD
2006
ACM
155views Data Mining» more  KDD 2006»
11 years 3 months ago
Single-pass online learning: performance, voting schemes and online feature selection
To learn concepts over massive data streams, it is essential to design inference and learning methods that operate in real time with limited memory. Online learning methods such a...
Vitor R. Carvalho, William W. Cohen
ICML
2007
IEEE
11 years 3 months ago
Winnowing subspaces
We generalize the Winnow algorithm for learning disjunctions to learning subspaces of low rank. Subspaces are represented by symmetric projection matrices. The online algorithm ma...
Manfred K. Warmuth
books