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LSSC
2001
Springer
15 years 4 months ago
A Quasi-Monte Carlo Method for Integration with Improved Convergence
Abstract. Quasi-Monte Carlo methods are based on the idea that random Monte Carlo techniques can often be improved by replacing the underlying source of random numbers with a more ...
Aneta Karaivanova, Ivan Dimov, Sofiya Ivanovska
CORR
2004
Springer
118views Education» more  CORR 2004»
14 years 11 months ago
Understanding Search Trees via Statistical Physics
We study the random m-ary search tree model (where m stands for the number of branches of the search tree), an important problem for data storage in computer science, using a varie...
Satya N. Majumdar, David S. Dean, Paul L. Krapivsk...
TIT
2010
97views Education» more  TIT 2010»
14 years 6 months ago
Why does the Kronecker model result in misleading capacity estimates?
Many recent works that study the performance of multi-input multi-output (MIMO) systems in practice assume a Kronecker model where the variances of the channel entries, upon decom...
Vasanthan Raghavan, Jayesh H. Kotecha, Akbar M. Sa...
98
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ICASSP
2011
IEEE
14 years 3 months ago
An acoustically-motivated spatial prior for under-determined reverberant source separation
We consider the task of under-determined reverberant audio source separation. We model the contribution of each source to all mixture channels in the time-frequency domain as a ze...
Ngoc Q. K. Duong, Emmanuel Vincent, Rémi Gr...
SAC
2006
ACM
15 years 5 months ago
The impact of sample reduction on PCA-based feature extraction for supervised learning
“The curse of dimensionality” is pertinent to many learning algorithms, and it denotes the drastic raise of computational complexity and classification error in high dimension...
Mykola Pechenizkiy, Seppo Puuronen, Alexey Tsymbal