Sciweavers

TSP
2010
13 years 6 months ago
Distributed spectrum sensing for cognitive radio networks by exploiting sparsity
Abstract--A cooperative approach to the sensing task of wireless cognitive radio (CR) networks is introduced based on a basis expansion model of the power spectral density (PSD) ma...
Juan Andrés Bazerque, Georgios B. Giannakis
SIAMJO
2010
125views more  SIAMJO 2010»
13 years 6 months ago
Trading Accuracy for Sparsity in Optimization Problems with Sparsity Constraints
We study the problem of minimizing the expected loss of a linear predictor while constraining its sparsity, i.e., bounding the number of features used by the predictor. While the r...
Shai Shalev-Shwartz, Nathan Srebro, Tong Zhang
INTERSPEECH
2010
13 years 7 months ago
Sparse component analysis for speech recognition in multi-speaker environment
Sparse Component Analysis is a relatively young technique that relies upon a representation of signal occupying only a small part of a larger space. Mixtures of sparse components ...
Afsaneh Asaei, Hervé Bourlard, Philip N. Ga...
ICCV
2009
IEEE
13 years 9 months ago
Learning with dynamic group sparsity
This paper investigates a new learning formulation called dynamic group sparsity. It is a natural extension of the standard sparsity concept in compressive sensing, and is motivat...
Junzhou Huang, Xiaolei Huang, Dimitris N. Metaxas
PKDD
2010
Springer
169views Data Mining» more  PKDD 2010»
13 years 10 months ago
Efficient and Numerically Stable Sparse Learning
We consider the problem of numerical stability and model density growth when training a sparse linear model from massive data. We focus on scalable algorithms that optimize certain...
Sihong Xie, Wei Fan, Olivier Verscheure, Jiangtao ...
EMNLP
2010
13 years 10 months ago
Simple Type-Level Unsupervised POS Tagging
Part-of-speech (POS) tag distributions are known to exhibit sparsity -- a word is likely to take a single predominant tag in a corpus. Recent research has demonstrated that incorp...
Yoong Keok Lee, Aria Haghighi, Regina Barzilay
TIP
2010
189views more  TIP 2010»
13 years 10 months ago
Image Inpainting by Patch Propagation Using Patch Sparsity
Abstract—This paper introduces a novel examplar-based inpainting algorithm through investigating the sparsity of natural image patches. Two novel concepts of sparsity at the patc...
Zongben Xu, Jian Sun
CORR
2007
Springer
116views Education» more  CORR 2007»
14 years 2 days ago
Non-Coherent Capacity and Reliability of Sparse Multipath Channels in the Wideband Regime
— In contrast to the prevalent assumption of rich multipath in information theoretic analysis of wireless channels, physical channels exhibit sparse multipath, especially at larg...
Gautham Hariharan, Akbar M. Sayeed
CORR
2007
Springer
111views Education» more  CORR 2007»
14 years 2 days ago
Capacity of Sparse Multipath Channels in the Ultra-Wideband Regime
—This paper studies the ergodic capacity of time- and frequency-selective multipath fading channels in the ultrawideband (UWB) regime when training signals are used for channel e...
Vasanthan Raghavan, Gautham Hariharan, Akbar M. Sa...
CORR
2007
Springer
110views Education» more  CORR 2007»
14 years 2 days ago
Information-theoretic limits on sparsity recovery in the high-dimensional and noisy setting
The problem of recovering the sparsity pattern of a fixed but unknown vector β∗ ∈ Rp based on a set of n noisy observations arises in a variety of settings, including subset...
Martin J. Wainwright