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» On regularization algorithms in learning theory
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169
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CIKM
2010
Springer
15 years 2 months ago
Regularization and feature selection for networked features
In the standard formalization of supervised learning problems, a datum is represented as a vector of features without prior knowledge about relationships among features. However, ...
Hongliang Fei, Brian Quanz, Jun Huan
COLING
2002
15 years 4 months ago
Unsupervised Learning of Generalized Names
We present an algorithm, Nomen, for learning generalized names in text. Examples of these are names of diseases and infectious agents, such as bacteria and viruses. These names ex...
Roman Yangarber, Winston Lin, Ralph Grishman
189
Voted
IDA
2008
Springer
15 years 4 months ago
Symbolic methodology for numeric data mining
Currently statistical and artificial neural network methods dominate in data mining applications. Alternative relational (symbolic) data mining methods have shown their effectivene...
Boris Kovalerchuk, Evgenii Vityaev
ISSAC
2007
Springer
112views Mathematics» more  ISSAC 2007»
15 years 10 months ago
G-graphs for the cage problem: a new upper bound
Constructing some regular graph with a given girth, a given degree and the fewest possible vertices is a hard problem. This problem is called the cage graph problem and has some l...
Alain Bretto, Luc Gillibert
CAV
1999
Springer
119views Hardware» more  CAV 1999»
15 years 8 months ago
A Theory of Restrictions for Logics and Automata
BDDs and their algorithms implement a decision procedure for Quanti ed Propositional Logic. BDDs are a kind of acyclic automata. Unrestricted automata (recognizing unbounded string...
Nils Klarlund