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» Modeling Classification and Inference Learning
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168
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AII
1992
15 years 5 months ago
Learning from Multiple Sources of Inaccurate Data
Most theoretical models of inductive inference make the idealized assumption that the data available to a learner is from a single and accurate source. The subject of inaccuracies ...
Ganesh Baliga, Sanjay Jain, Arun Sharma
117
Voted
KDD
2009
ACM
204views Data Mining» more  KDD 2009»
16 years 1 months ago
Improving classification accuracy using automatically extracted training data
Classification is a core task in knowledge discovery and data mining, and there has been substantial research effort in developing sophisticated classification models. In a parall...
Ariel Fuxman, Anitha Kannan, Andrew B. Goldberg, R...
123
Voted
APN
2010
Springer
14 years 11 months ago
Learning Workflow Petri Nets
Workflow mining is the task of automatically producing a workflow model from a set of event logs recording sequences of workflow events; each sequence corresponds to a use case or ...
Javier Esparza, Martin Leucker, Maximilian Schlund
101
Voted
COLT
2004
Springer
15 years 6 months ago
Learning Classes of Probabilistic Automata
Abstract. Probabilistic finite automata (PFA) model stochastic languages, i.e. probability distributions over strings. Inferring PFA from stochastic data is an open field of rese...
François Denis, Yann Esposito
136
Voted
ICML
2009
IEEE
16 years 1 months ago
Exploiting sparse Markov and covariance structure in multiresolution models
We consider Gaussian multiresolution (MR) models in which coarser, hidden variables serve to capture statistical dependencies among the finest scale variables. Tree-structured MR ...
Myung Jin Choi, Venkat Chandrasekaran, Alan S. Wil...