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ISDA
2010
IEEE
15 years 4 months ago
Avoiding simplification strategies by introducing multi-objectiveness in real world problems
Abstract--In business analysis, models are sometimes oversimplified. We pragmatically approach many problems with a single financial objective and include monetary values for non-m...
Charlotte J. C. Rietveld, Gijs P. Hendrix, Frank T...
AAAI
2008
15 years 7 months ago
Bimodal Spatial Reasoning with Continuous Motion
Symbolic AI systems typically have difficulty reasoning about motion in continuous environments, such as determining whether a cornering car will clear a close obstacle. Bimodal s...
Samuel Wintermute, John E. Laird
GLOBECOM
2007
IEEE
16 years 1 months ago
Reduced Complexity Sphere Decoding for Square QAM via a New Lattice Representation
— Sphere decoding (SD) is a low complexity maximum likelihood (ML) detection algorithm, which has been adapted for different linear channels in digital communications. The comple...
Luay Azzam, Ender Ayanoglu
ICML
2006
IEEE
16 years 7 months ago
Convex optimization techniques for fitting sparse Gaussian graphical models
We consider the problem of fitting a large-scale covariance matrix to multivariate Gaussian data in such a way that the inverse is sparse, thus providing model selection. Beginnin...
Onureena Banerjee, Laurent El Ghaoui, Alexandre d'...
ALDT
2009
Springer
142views Algorithms» more  ALDT 2009»
16 years 1 months ago
Finding Best k Policies
Abstract. An optimal probabilistic-planning algorithm solves a problem, usually modeled by a Markov decision process, by finding its optimal policy. In this paper, we study the k ...
Peng Dai, Judy Goldsmith