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KDD
2008
ACM
115views Data Mining» more  KDD 2008»
14 years 7 months ago
SPIRAL: efficient and exact model identification for hidden Markov models
Hidden Markov models (HMMs) have received considerable attention in various communities (e.g, speech recognition, neurology and bioinformatic) since many applications that use HMM...
Yasuhiro Fujiwara, Yasushi Sakurai, Masashi Yamamu...
ACM
1995
13 years 11 months ago
Rough Sets
We study properties of rough sets, that is, approximations to sets of records in a database or, more formally, to subsets of the universe of an information system. A rough set is a...
Zdzislaw Pawlak
JMLR
2010
157views more  JMLR 2010»
13 years 2 months ago
Why are DBNs sparse?
Real stochastic processes operating in continuous time can be modeled by sets of stochastic differential equations. On the other hand, several popular model families, including hi...
Shaunak Chatterjee, Stuart Russell
SOCO
2010
Springer
13 years 2 months ago
Using evolution strategies to solve DEC-POMDP problems
Decentralized partially observable Markov decision process (DEC-POMDP) is an approach to model multi-robot decision making problems under uncertainty. Since it is NEXP-complete the...
Baris Eker, H. Levent Akin
PODS
2011
ACM
220views Database» more  PODS 2011»
12 years 10 months ago
Maximizing conjunctive views in deletion propagation
In deletion propagation, tuples from the database are deleted in order to reflect the deletion of a tuple from the view. Such an operation may result in the (often necessary) del...
Benny Kimelfeld, Jan Vondrák, Ryan Williams