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» Sublinear Optimization for Machine Learning
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AAAI
2007
14 years 14 days ago
Learning to Solve QBF
We present a novel approach to solving Quantified Boolean Formulas (QBF) that combines a search-based QBF solver with machine learning techniques. We show how classification met...
Horst Samulowitz, Roland Memisevic
ECML
2006
Springer
14 years 1 months ago
Ensembles of Nearest Neighbor Forecasts
Nearest neighbor forecasting models are attractive with their simplicity and the ability to predict complex nonlinear behavior. They rely on the assumption that observations simila...
Dragomir Yankov, Dennis DeCoste, Eamonn J. Keogh
ICML
2005
IEEE
14 years 11 months ago
Robust one-class clustering using hybrid global and local search
Unsupervised learning methods often involve summarizing the data using a small number of parameters. In certain domains, only a small subset of the available data is relevant for ...
Gunjan Gupta, Joydeep Ghosh
GECCO
2005
Springer
136views Optimization» more  GECCO 2005»
14 years 3 months ago
Preventing overfitting in GP with canary functions
Overfitting is a fundamental problem of most machine learning techniques, including genetic programming (GP). Canary functions have been introduced in the literature as a concept ...
Nate Foreman, Matthew P. Evett
ML
2006
ACM
131views Machine Learning» more  ML 2006»
13 years 10 months ago
Markov logic networks
We propose a simple approach to combining first-order logic and probabilistic graphical models in a single representation. A Markov logic network (MLN) is a first-order knowledge b...
Matthew Richardson, Pedro Domingos