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ICRA
2005
IEEE
150views Robotics» more  ICRA 2005»
13 years 11 months ago
Learning Sensor Network Topology through Monte Carlo Expectation Maximization
— We consider the problem of inferring sensor positions and a topological (i.e. qualitative) map of an environment given a set of cameras with non-overlapping fields of view. In...
Dimitri Marinakis, Gregory Dudek, David J. Fleet
CVPR
2004
IEEE
14 years 7 months ago
Atlanta World: An Expectation Maximization Framework for Simultaneous Low-Level Edge Grouping and Camera Calibration in Complex
Edges in man-made environments, grouped according to vanishing point directions, provide single-view constraints that have been exploited before as a precursor to both scene under...
Grant Schindler, Frank Dellaert
ICDM
2009
IEEE
137views Data Mining» more  ICDM 2009»
14 years 6 days ago
A Local Scalable Distributed Expectation Maximization Algorithm for Large Peer-to-Peer Networks
This paper offers a local distributed algorithm for expectation maximization in large peer-to-peer environments. The algorithm can be used for a variety of well-known data mining...
Kanishka Bhaduri, Ashok N. Srivastava
BMCBI
2008
120views more  BMCBI 2008»
13 years 5 months ago
E-CAI: a novel server to estimate an expected value of Codon Adaptation Index (eCAI)
Background: The Codon Adaptation Index (CAI) is a measure of the synonymous codon usage bias for a DNA or RNA sequence. It quantifies the similarity between the synonymous codon u...
Pere Puigbò, Ignacio G. Bravo, Santiago Gar...
ATAL
2006
Springer
13 years 9 months ago
Sequences of take-it-or-leave-it offers: near-optimal auctions without full valuation revelation
Abstract. We introduce take-it-or-leave-it auctions (TLAs) as an allocation mechanism that allows buyers to retain much of their private valuation information, yet generates close-...
Tuomas Sandholm, Andrew Gilpin