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» A Discourse on Complexity of Process Models
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GECCO
2009
Springer
148views Optimization» more  GECCO 2009»
15 years 2 months ago
Genetic programming for quantitative stock selection
We provide an overview of using genetic programming (GP) to model stock returns. Our models employ GP terminals (model decision variables) that are financial factors identified by...
Ying L. Becker, Una-May O'Reilly
ICCV
2011
IEEE
14 years 4 months ago
A Nonparametric Riemannian Framework on Tensor Field with Application to Foreground Segmentation
Background modelling on tensor field has recently been proposed for foreground detection tasks. Taking into account the Riemannian structure of the tensor manifold, recent resear...
Rui Caseiro, João F. Henriques, Pedro Martins, Jo...
ECCV
2008
Springer
16 years 6 months ago
Unsupervised Structure Learning: Hierarchical Recursive Composition, Suspicious Coincidence and Competitive Exclusion
Abstract. We describe a new method for unsupervised structure learning of a hierarchical compositional model (HCM) for deformable objects. The learning is unsupervised in the sense...
Long Zhu, Chenxi Lin, Haoda Huang, Yuanhao Chen, A...
154
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JUCS
2010
109views more  JUCS 2010»
14 years 11 months ago
Semantics of Query-Driven Communication of Exact Values
: We address the question of how to communicate among distributed processes values such as real numbers, continuous functions and geometrical solids with arbitrary precision, yet e...
Michal Konecný, Amin Farjudian
CAD
2005
Springer
15 years 4 months ago
Bayesian computer-aided experimental design of heterogeneous scaffolds for tissue engineering
This paper presents a Bayesian methodology for computer-aided experimental design of heterogeneous scaffolds for tissue engineering applications. These heterogeneous scaffolds hav...
Lee E. Weiss, Cristina H. Amon, Susan Finger, Eric...