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» Computing with Infinitely Many Processes
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ICIP
2003
IEEE
14 years 10 months ago
Fast GEM wavelet-based image deconvolution algorithm
The paper proposes a new wavelet-based Bayesian approach to image deconvolution, under the space-invariant blur and additive white Gaussian noise assumptions. Image deconvolution ...
José M. Bioucas-Dias
ACSD
2010
IEEE
215views Hardware» more  ACSD 2010»
13 years 6 months ago
A Formal Semantics of Clock Refinement in Imperative Synchronous Languages
The synchronous model of computation divides the execution of a program into an infinite sequence of socalled macro steps, which are further divided into finitely many micro steps....
Mike Gemunde, Jens Brandt, Klaus Schneider
KDD
2008
ACM
119views Data Mining» more  KDD 2008»
14 years 9 months ago
SAIL: summation-based incremental learning for information-theoretic clustering
Information-theoretic clustering aims to exploit information theoretic measures as the clustering criteria. A common practice on this topic is so-called INFO-K-means, which perfor...
Junjie Wu, Hui Xiong, Jian Chen
IPOM
2007
Springer
14 years 2 months ago
Measurement and Analysis of Intraflow Performance Characteristics of Wireless Traffic
It is by now widely accepted that the arrival process of aggregate network traffic exhibits self-similar characteristics which result in the preservation of traffic burstiness (hig...
Dimitrios P. Pezaros, Manolis Sifalakis, David Hut...
CORR
2012
Springer
183views Education» more  CORR 2012»
12 years 4 months ago
Learning Determinantal Point Processes
Determinantal point processes (DPPs), which arise in random matrix theory and quantum physics, are natural models for subset selection problems where diversity is preferred. Among...
Alex Kulesza, Ben Taskar