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» Declarative Data Cleaning: Language, Model, and Algorithms
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DAGSTUHL
1997
13 years 10 months ago
Querying the Uncertain Position of Moving Objects
In this paper we propose a data model for representing moving objects with uncertain positions in database systems. It is called the Moving Objects Spatio-Temporal (MOST) data mod...
A. Prasad Sistla, Ouri Wolfson, Sam Chamberlain, S...
COLT
1992
Springer
14 years 29 days ago
Language Learning from Stochastic Input
Language learning from positive data in the Gold model of inductive inference is investigated in a setting where the data can be modeled as a stochastic process. Specifically, the...
Shyam Kapur, Gianfranco Bilardi
JMLR
2010
134views more  JMLR 2010»
13 years 3 months ago
Using Contextual Representations to Efficiently Learn Context-Free Languages
We present a polynomial update time algorithm for the inductive inference of a large class of context-free languages using the paradigm of positive data and a membership oracle. W...
Alexander Clark, Rémi Eyraud, Amaury Habrar...
JMLR
2012
11 years 11 months ago
Bounding the Probability of Error for High Precision Optical Character Recognition
We consider a model for which it is important, early in processing, to estimate some variables with high precision, but perhaps at relatively low recall. If some variables can be ...
Gary B. Huang, Andrew Kae, Carl Doersch, Erik G. L...
AAAI
1998
13 years 10 months ago
Probabilistic Frame-Based Systems
Two of the most important threads of work in knowledge representation today are frame-based representation systems (FRS's) and Bayesian networks (BNs). FRS's provide an ...
Daphne Koller, Avi Pfeffer