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JCST
2010
189views more  JCST 2010»
13 years 2 months ago
Formally Analyzing Expected Time Complexity of Algorithms Using Theorem Proving
Probabilistic techniques are widely used in the analysis of algorithms to estimate the computational complexity of algorithms or a computational problem. Traditionally, such analys...
Osman Hasan, Sofiène Tahar
TKDE
2002
166views more  TKDE 2002»
13 years 7 months ago
A Comprehensive Analytical Performance Model for Disk Devices under Random Workloads
Our goal with this paper is to contribute a common theoretical framework for studying the performance of disk-storage devices. Understanding the performance behavior of these devi...
Peter Triantafillou, Stavros Christodoulakis, Cost...
IJCNN
2007
IEEE
14 years 1 months ago
Generalised Kernel Machines
Abstract— The generalised linear model (GLM) is the standard approach in classical statistics for regression tasks where it is appropriate to measure the data misfit using a lik...
Gavin C. Cawley, Gareth J. Janacek, Nicola L. C. T...
QUESTA
2007
117views more  QUESTA 2007»
13 years 7 months ago
Estimating tail probabilities of heavy tailed distributions with asymptotically zero relative error
Efficient estimation of tail probabilities involving heavy tailed random variables is amongst the most challenging problems in Monte-Carlo simulation. In the last few years, appli...
Sandeep Juneja
TSP
2008
151views more  TSP 2008»
13 years 7 months ago
Convergence Analysis of Reweighted Sum-Product Algorithms
Markov random fields are designed to represent structured dependencies among large collections of random variables, and are well-suited to capture the structure of real-world sign...
Tanya Roosta, Martin J. Wainwright, Shankar S. Sas...