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» New Algorithms for Learning in Presence of Errors
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IJCAI
1989
13 years 9 months ago
Generating Better Decision Trees
A new decision tree learning algorithm called IDX is described. More general than existing algorithms, IDX addresses issues of decision tree quality largely overlooked in the arti...
Steven W. Norton
WEBDB
2010
Springer
178views Database» more  WEBDB 2010»
14 years 1 months ago
Using Latent-Structure to Detect Objects on the Web
An important requirement for emerging applications which aim to locate and integrate content distributed over the Web is to identify pages that are relevant for a given domain or ...
Luciano Barbosa, Juliana Freire
PVLDB
2010
99views more  PVLDB 2010»
13 years 7 months ago
Towards Certain Fixes with Editing Rules and Master Data
A variety of integrity constraints have been studied for data cleaning. While these constraints can detect the presence of errors, they fall short of guiding us to correct the err...
Wenfei Fan, Jianzhong Li, Shuai Ma, Nan Tang, Weny...
ICML
2005
IEEE
14 years 9 months ago
A model for handling approximate, noisy or incomplete labeling in text classification
We introduce a Bayesian model, BayesANIL, that is capable of estimating uncertainties associated with the labeling process. Given a labeled or partially labeled training corpus of...
Ganesh Ramakrishnan, Krishna Prasad Chitrapura, Ra...
CORR
2011
Springer
243views Education» more  CORR 2011»
13 years 3 months ago
Localization from Incomplete Noisy Distance Measurements
—We consider the problem of positioning a cloud of points in the Euclidean space Rd , from noisy measurements of a subset of pairwise distances. This task has applications in var...
Adel Javanmard, Andrea Montanari