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» Approximate Join Processing Over Data Streams
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ICML
1999
IEEE
14 years 9 months ago
Monte Carlo Hidden Markov Models: Learning Non-Parametric Models of Partially Observable Stochastic Processes
We present a learning algorithm for non-parametric hidden Markov models with continuous state and observation spaces. All necessary probability densities are approximated using sa...
Sebastian Thrun, John Langford, Dieter Fox
SADM
2008
178views more  SADM 2008»
13 years 8 months ago
Fast Projection-Based Methods for the Least Squares Nonnegative Matrix Approximation Problem
: Nonnegative matrix approximation (NNMA) is a popular matrix decomposition technique that has proven to be useful across a diverse variety of fields with applications ranging from...
Dongmin Kim, Suvrit Sra, Inderjit S. Dhillon
RCIS
2010
13 years 7 months ago
A Tree-based Approach for Efficiently Mining Approximate Frequent Itemsets
—The strategies for mining frequent itemsets, which is the essential part of discovering association rules, have been widely studied over the last decade. In real-world datasets,...
Jia-Ling Koh, Yi-Lang Tu
ISEMANTICS
2010
13 years 10 months ago
Live linked open sensor database
There are millions of sensors being deployed all over the world. Data generated by these sensors is provided in different formats and interfaces and is rarely associated with sema...
Danh Le Phuoc, Josiane Xavier Parreira, Michael Ha...
WWW
2008
ACM
14 years 9 months ago
Efficiently querying rdf data in triple stores
Efficiently querying RDF [1] data is being an important factor in applying Semantic Web technologies to real-world applications. In this context, many efforts have been made to st...
Ying Yan, Chen Wang, Aoying Zhou, Weining Qian, Li...