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ICML
1999
IEEE
14 years 8 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
STOC
2009
ACM
123views Algorithms» more  STOC 2009»
14 years 8 months ago
An improved constant-time approximation algorithm for maximum~matchings
This paper studies constant-time approximation algorithms for problems on degree-bounded graphs. Let n and d be the number of vertices and the degree bound, respectively. This pap...
Yuichi Yoshida, Masaki Yamamoto, Hiro Ito
PODC
2009
ACM
14 years 8 months ago
A distributed polylogarithmic time algorithm for self-stabilizing skip graphs
Peer-to-peer systems rely on scalable overlay networks that enable efficient routing between its members. Hypercubic topologies facilitate such operations while each node only nee...
Riko Jacob, Andréa W. Richa, Christian Sche...
KDD
2004
ACM
207views Data Mining» more  KDD 2004»
14 years 8 months ago
SPIN: mining maximal frequent subgraphs from graph databases
One fundamental challenge for mining recurring subgraphs from semi-structured data sets is the overwhelming abundance of such patterns. In large graph databases, the total number ...
Jun Huan, Wei Wang 0010, Jan Prins, Jiong Yang
RECOMB
2007
Springer
14 years 8 months ago
Network Motif Discovery Using Subgraph Enumeration and Symmetry-Breaking
The study of biological networks and network motifs can yield significant new insights into systems biology. Previous methods of discovering network motifs ? network-centric subgra...
Joshua A. Grochow, Manolis Kellis