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» Reformulating Constraint Models Using Input Data
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IJCNN
2007
IEEE
15 years 4 months ago
Agnostic Learning versus Prior Knowledge in the Design of Kernel Machines
Abstract— The optimal model parameters of a kernel machine are typically given by the solution of a convex optimisation problem with a single global optimum. Obtaining the best p...
Gavin C. Cawley, Nicola L. C. Talbot
MSWIM
2005
ACM
15 years 3 months ago
Adaptive transmission opportunity with admission control for IEEE 802.11e networks
The increase of IEEE 802.11’s bandwidth led to a deployment of many multimedia applications over wireless networks. Nevertheless, these applications impose stringent constraints...
Adlen Ksentini, Abdelhak Guéroui, Mohamed N...
BMCBI
2008
173views more  BMCBI 2008»
14 years 9 months ago
Gene Vector Analysis (Geneva): A unified method to detect differentially-regulated gene sets and similar microarray experiments
Background: Microarray experiments measure changes in the expression of thousands of genes. The resulting lists of genes with changes in expression are then searched for biologica...
Stephen W. Tanner, Pankaj Agarwal
POPL
2008
ACM
15 years 10 months ago
Imperative self-adjusting computation
Self-adjusting computation enables writing programs that can automatically and efficiently respond to changes to their data (e.g., inputs). The idea behind the approach is to stor...
Umut A. Acar, Amal Ahmed, Matthias Blume
CVPR
2004
IEEE
15 years 11 months ago
High-Zoom Video Hallucination by Exploiting Spatio-Temporal Regularities
In this paper, we consider the problem of super-resolving a human face video by a very high (?16) zoom factor. Inspired by recent literature on hallucination and examplebased lear...
Göksel Dedeoglu, Jonas August, Takeo Kanade