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» Iterated importance sampling in missing data problems
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91
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PR
2006
229views more  PR 2006»
14 years 11 months ago
FS_SFS: A novel feature selection method for support vector machines
In many pattern recognition applications, high-dimensional feature vectors impose a high computational cost as well as the risk of "overfitting". Feature Selection addre...
Yi Liu, Yuan F. Zheng
82
Voted
ICMCS
2005
IEEE
110views Multimedia» more  ICMCS 2005»
15 years 4 months ago
Estimating Packet Arrival Times in Bursty Video Applications
In retransmission-based error-control methods, the most fundamental yet the paramount problem is to determine how long the sender (or the receiver) should wait before deciding tha...
Ali C. Begen, Yucel Altunbasak
MM
1997
ACM
112views Multimedia» more  MM 1997»
15 years 3 months ago
An Evaluation of VBR Disk Admission Algorithms for Continuous Media File Servers
In this paper, we address the problem of choosing a disk admission algorithm for continuous media streams where each stream may have a di erent bit rate, and more importantly, whe...
Dwight J. Makaroff, Gerald W. Neufeld, Norman C. H...
EUROMICRO
2004
IEEE
15 years 2 months ago
Predicting Real-Time Properties of Component Assemblies: A Scenario-Simulation Approach
This paper addresses the problem of predicting timing properties of multi-tasking component assemblies during the design phase. For real-time applications, it is of vital importan...
Egor Bondarev, Johan Muskens, Peter H. N. de With,...
NPL
2006
85views more  NPL 2006»
14 years 11 months ago
A Neural Model for Context-dependent Sequence Learning
A novel neural network model is described that implements context-dependent learning of complex sequences. The model utilises leaky integrate-and-fire neurons to extract timing inf...
Luc Berthouze, Adriaan G. Tijsseling