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JMLR
2008
209views more  JMLR 2008»
13 years 7 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
GLOBECOM
2009
IEEE
14 years 2 months ago
Sparse Decoding of Low Density Parity Check Codes Using Margin Propagation
—One of the key factors underlying the popularity of Low-density parity-check (LDPC) code is its iterative decoding algorithm that is amenable to efficient hardware implementati...
Ming Gu, Kiran Misra, Hayder Radha, Shantanu Chakr...
MIR
2010
ACM
229views Multimedia» more  MIR 2010»
14 years 2 months ago
Wavelet, active basis, and shape script: a tour in the sparse land
Sparse coding is a key principle that underlies wavelet representation of natural images. In this paper, we explain that the effort of seeking a common wavelet sparse coding of i...
Zhangzhang Si, Ying Nian Wu
FOCS
2000
IEEE
13 years 11 months ago
Efficient Algorithms for Universal Portfolios
A constant rebalanced portfolio is an investment strategy that keeps the same distribution of wealth among a set of stocks from day to day. There has been much work on Cover'...
Adam Kalai, Santosh Vempala
TNN
2010
148views Management» more  TNN 2010»
13 years 2 months ago
Generalized low-rank approximations of matrices revisited
Compared to Singular Value Decomposition (SVD), Generalized Low Rank Approximations of Matrices (GLRAM) can consume less computation time, obtain higher compression ratio, and yiel...
Jun Liu, Songcan Chen, Zhi-Hua Zhou, Xiaoyang Tan