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ICASSP
2011
IEEE
12 years 10 months ago
Empirical divergence maximization for quantizer design: An analysis of approximation error
Empirical divergence maximization is an estimation method similar to empirical risk minimization whereby the Kullback-Leibler divergence is maximized over a class of functions tha...
Michael A. Lexa
ESWA
2011
220views Database» more  ESWA 2011»
12 years 10 months ago
Unsupervised neural models for country and political risk analysis
This interdisciplinary research project focuses on relevant applications of Knowledge Discovery and Artificial Neural Networks in order to identify and analyse levels of country, b...
Álvaro Herrero, Emilio Corchado, Alfredo Ji...
HICSS
2007
IEEE
162views Biometrics» more  HICSS 2007»
14 years 1 months ago
Value-at-Risk in IT Services Contracts
As information systems (IS) and technology solutions become increasingly service-driven, managers are faced with the task of choosing parameters such as service-levels, pricing, a...
Robert J. Kauffman, Ryan Sougstad
ICML
2009
IEEE
14 years 8 months ago
Polyhedral outer approximations with application to natural language parsing
Recent approaches to learning structured predictors often require approximate inference for tractability; yet its effects on the learned model are unclear. Meanwhile, most learnin...
André F. T. Martins, Noah A. Smith, Eric P....
UAI
2001
13 years 8 months ago
Iterative Markov Chain Monte Carlo Computation of Reference Priors and Minimax Risk
We present an iterative Markov chain Monte Carlo algorithm for computing reference priors and minimax risk for general parametric families. Our approach uses MCMC techniques based...
John D. Lafferty, Larry A. Wasserman