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ICMLA
2007
15 years 8 months ago
Maximum Likelihood Quantization of Genomic Features Using Dynamic Programming
Dynamic programming is introduced to quantize a continuous random variable into a discrete random variable. Quantization is often useful before statistical analysis or reconstruct...
Mingzhou (Joe) Song, Robert M. Haralick, Sté...
TOG
2008
200views more  TOG 2008»
15 years 6 months ago
Improved seam carving for video retargeting
Video, like images, should support content aware resizing. We present video retargeting using an improved seam carving operator. Instead of removing 1D seams from 2D images we rem...
Michael Rubinstein, Ariel Shamir, Shai Avidan
IJON
2010
138views more  IJON 2010»
15 years 5 months ago
A dynamic Bayesian network to represent discrete duration models
Originally devoted to specific applications such as biology, medicine and demography, duration models are now widely used in economy, finance or reliability. Recent works in var...
Roland Donat, Philippe Leray, Laurent Bouillaut, P...
FOCS
1991
IEEE
15 years 10 months ago
Dynamic Three-Dimensional Linear Programming
We perform linear programming optimizations on the intersection of k polyhedra in R3 , represented by their outer recursive decompositions, in expected time O(k log k log n + √ ...
David Eppstein
COCOA
2009
Springer
15 years 11 months ago
On Open Rectangle-of-Influence Drawings of Planar Graphs
: Under water sensor network is an important research direction in computer science. There are many interesting optimization problems regarding its design, routing and applications...
Huaming Zhang, Milind Vaidya