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GECCO
2006
Springer
206views Optimization» more  GECCO 2006»
14 years 15 days ago
Adaptive discretization for probabilistic model building genetic algorithms
This paper proposes an adaptive discretization method, called Split-on-Demand (SoD), to enable the probabilistic model building genetic algorithm (PMBGA) to solve optimization pro...
Chao-Hong Chen, Wei-Nan Liu, Ying-Ping Chen
IJCV
2000
164views more  IJCV 2000»
13 years 8 months ago
Probabilistic Modeling and Recognition of 3-D Objects
This paper introduces a uniform statistical framework for both 3-D and 2-D object recognition using intensity images as input data. The theoretical part provides a mathematical too...
Joachim Hornegger, Heinrich Niemann
EMNLP
2010
13 years 6 months ago
Inducing Probabilistic CCG Grammars from Logical Form with Higher-Order Unification
This paper addresses the problem of learning to map sentences to logical form, given training data consisting of natural language sentences paired with logical representations of ...
Tom Kwiatkowksi, Luke S. Zettlemoyer, Sharon Goldw...
ICML
2008
IEEE
14 years 9 months ago
Efficiently learning linear-linear exponential family predictive representations of state
Exponential Family PSR (EFPSR) models capture stochastic dynamical systems by representing state as the parameters of an exponential family distribution over a shortterm window of...
David Wingate, Satinder P. Singh
SEAL
2010
Springer
13 years 7 months ago
Bayesian Reliability Analysis under Incomplete Information Using Evolutionary Algorithms
During engineering design, it is often difficult to quantify product reliability because of insufficient data or information for modeling the uncertainties. In such cases, one need...
Rupesh Kumar Srivastava, Kalyanmoy Deb