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142
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JMLR
2006
143views more  JMLR 2006»
15 years 3 months ago
Segmental Hidden Markov Models with Random Effects for Waveform Modeling
This paper proposes a general probabilistic framework for shape-based modeling and classification of waveform data. A segmental hidden Markov model (HMM) is used to characterize w...
Seyoung Kim, Padhraic Smyth
118
Voted
JMLR
2000
134views more  JMLR 2000»
15 years 3 months ago
Learning with Mixtures of Trees
This paper describes the mixtures-of-trees model, a probabilistic model for discrete multidimensional domains. Mixtures-of-trees generalize the probabilistic trees of Chow and Liu...
Marina Meila, Michael I. Jordan
122
Voted
GECCO
2009
Springer
117views Optimization» more  GECCO 2009»
15 years 8 months ago
BBOB-benchmarking a simple estimation of distribution algorithm with cauchy distribution
The restarted estimation of distribution algorithm (EDA) with Cauchy distribution as the probabilistic model is tested on the BBOB 2009 testbed. These tests prove that when using ...
Petr Posik
105
Voted
GECCO
2004
Springer
15 years 9 months ago
Modeling Selection Intensity for Toroidal Cellular Evolutionary Algorithms
We present quantitative models for the selection pressure of cellular evolutionary algorithms structured in two dimensional regular lattices. We derive models based on probabilisti...
Mario Giacobini, Enrique Alba, Andrea Tettamanzi, ...
136
Voted
ICML
2005
IEEE
16 years 4 months ago
Learning first-order probabilistic models with combining rules
Many real-world domains exhibit rich relational structure and stochasticity and motivate the development of models that combine predicate logic with probabilities. These models de...
Sriraam Natarajan, Prasad Tadepalli, Eric Altendor...