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TIT
2010
174views Education» more  TIT 2010»
14 years 11 months ago
Toeplitz Compressed Sensing Matrices With Applications to Sparse Channel Estimation
Compressed sensing (CS) has recently emerged as a powerful signal acquisition paradigm. In essence, CS enables the recovery of high-dimensional sparse signals from relatively few ...
Jarvis Haupt, Waheed Uz Zaman Bajwa, Gil M. Raz, R...
KDD
2012
ACM
235views Data Mining» more  KDD 2012»
13 years 7 months ago
A near-linear time approximation algorithm for angle-based outlier detection in high-dimensional data
Outlier mining in d-dimensional point sets is a fundamental and well studied data mining task due to its variety of applications. Most such applications arise in high-dimensional ...
Ninh Pham, Rasmus Pagh
CSMR
2004
IEEE
15 years 8 months ago
Supporting Architectural Restructuring by Analyzing Feature Models
In order to lower the risk, reengineering projects aim at high reuse rates. Therefore, tasks like architectural restructuring have to be performed in a way that developed new syst...
Ilian Pashov, Matthias Riebisch, Ilka Philippow
DGO
2006
136views Education» more  DGO 2006»
15 years 5 months ago
Automated classification of congressional legislation
For social science researchers, content analysis and classification of United States Congressional legislative activities has been time consuming and costly. The Library of Congre...
Stephen Purpura, Dustin Hillard
ACCV
2006
Springer
15 years 10 months ago
Statistical Shape Models Using Elastic-String Representations
Abstract. To develop statistical models for shapes, we utilize an elastic string representation where curves (denoting shapes) can bend and locally stretch (or compress) to optimal...
Anuj Srivastava, Aastha Jain, Shantanu H. Joshi, D...