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UAI
2003
15 years 8 months ago
Learning Continuous Time Bayesian Networks
Continuous time Bayesian networks (CTBN) describe structured stochastic processes with finitely many states that evolve over continuous time. A CTBN is a directed (possibly cycli...
Uri Nodelman, Christian R. Shelton, Daphne Koller
JASIS
2010
121views more  JASIS 2010»
15 years 5 months ago
Linear time series models for term weighting in information retrieval
Common measures of term importance in information retrieval (IR) rely on counts of term frequency; rare terms receive higher weight in document ranking than common terms receive. ...
Miles Efron
IMC
2003
ACM
15 years 11 months ago
Variability in TCP round-trip times
We measured and analyzed the variability in round trip times (RTTs) within TCP connections using passive measurement techniques. We collected eight hours of bidirectional traces c...
Jay Aikat, Jasleen Kaur, F. Donelson Smith, Kevin ...
AUSDM
2006
Springer
94views Data Mining» more  AUSDM 2006»
15 years 10 months ago
Marking Time in Sequence Mining
Sequence mining is often conducted over static and temporal datasets as well as over collections of events (episodes). More recently, there has also been a focus on the mining of ...
Carl Mooney, John F. Roddick
NIPS
2007
15 years 8 months ago
TrueSkill Through Time: Revisiting the History of Chess
We extend the Bayesian skill rating system TrueSkill to infer entire time series of skills of players by smoothing through time instead of filtering. The skill of each participat...
Pierre Dangauthier, Ralf Herbrich, Tom Minka, Thor...