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ECML
1993
Springer
15 years 11 months ago
Complexity Dimensions and Learnability
In machine learning theory, problem classes are distinguished because of di erences in complexity. In 6 , a stochastic model of learning from examples was introduced. This PAClear...
Shan-Hwei Nienhuys-Cheng, Mark Polman
ASMTA
2009
Springer
114views Mathematics» more  ASMTA 2009»
15 years 11 months ago
Improving the Efficiency of the Proxel Method by Using Individual Time Steps
Discrete stochastic models (DSM) are widely used in various application fields today. Proxel-based simulation can outperform discrete event-based approaches in the analysis of smal...
Claudia Krull, Robert Buchholz, Graham Horton
COCOA
2009
Springer
15 years 11 months ago
Positive Influence Dominating Set in Online Social Networks
Online social network has developed significantly in recent years as a medium of communicating, sharing and disseminating information and spreading influence. Most of current resea...
Feng Wang 0002, Erika Camacho, Kuai Xu
ECML
2006
Springer
15 years 10 months ago
Deconvolutive Clustering of Markov States
In this paper we formulate the problem of grouping the states of a discrete Markov chain of arbitrary order simultaneously with deconvolving its transition probabilities. As the na...
Ata Kabán, Xin Wang
RSCTC
2000
Springer
126views Fuzzy Logic» more  RSCTC 2000»
15 years 10 months ago
Evolutionary Parsing for a Probabilistic Context Free Grammar
Abstract. Classic parsing methods are based on complete search techniques to find the different interpretations of a sentence. However, the size of the search space increases expon...
Lourdes Araujo