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TWC
2010
14 years 6 months ago
Optimized Training Sequences for Spatially Correlated MIMO-OFDM
In this paper, the training sequence design for multiple-input multiple-output (MIMO) orthogonal frequencydivision multiplexing (OFDM) systems under the minimum mean square error (...
Hoang Duong Tuan, Ha Hoang Kha, Ha H. Nguyen, Viet...

Book
5396views
16 years 10 months ago
Markov Random Field Modeling in Computer Vision
Markov random field (MRF) theory provides a basis for modeling contextual constraints in visual processing and interpretation. It enables us to develop optimal vision algorithms sy...
Stan Z. Li
CORR
2011
Springer
202views Education» more  CORR 2011»
14 years 6 months ago
Noisy matrix decomposition via convex relaxation: Optimal rates in high dimensions
We analyze a class of estimators based on a convex relaxation for solving highdimensional matrix decomposition problems. The observations are the noisy realizations of the sum of ...
Alekh Agarwal, Sahand Negahban, Martin J. Wainwrig...
SMA
2008
ACM
122views Solid Modeling» more  SMA 2008»
14 years 11 months ago
The cost of not knowing the radius
Robust Statistics considers the quality of statistical decisions in the presence of deviations from the ideal model, where deviations are modelled by neighborhoods of a certain siz...
Helmut Rieder, Matthias Kohl, Peter Ruckdeschel
JMLR
2008
209views more  JMLR 2008»
14 years 12 months ago
Bayesian Inference and Optimal Design for the Sparse Linear Model
The linear model with sparsity-favouring prior on the coefficients has important applications in many different domains. In machine learning, most methods to date search for maxim...
Matthias W. Seeger