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» Handling Sparse Data by Successive Abstraction
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TNN
2010
176views Management» more  TNN 2010»
13 years 4 months ago
Sparse approximation through boosting for learning large scale kernel machines
Abstract--Recently, sparse approximation has become a preferred method for learning large scale kernel machines. This technique attempts to represent the solution with only a subse...
Ping Sun, Xin Yao
TSP
2010
13 years 4 months ago
Sparse channel estimation for multicarrier underwater acoustic communication: from subspace methods to compressed sensing
Abstract--In this paper, we investigate various channel estimators that exploit channel sparsity in the time and/or Doppler domain for a multicarrier underwater acoustic system. We...
Christian R. Berger, Shengli Zhou, James C. Preisi...
SCIA
2009
Springer
305views Image Analysis» more  SCIA 2009»
14 years 4 months ago
A Convex Approach to Low Rank Matrix Approximation with Missing Data
Many computer vision problems can be formulated as low rank bilinear minimization problems. One reason for the success of these problems is that they can be efficiently solved usin...
Carl Olsson, Magnus Oskarsson
SIGIR
2006
ACM
14 years 3 months ago
Latent semantic analysis for multiple-type interrelated data objects
Co-occurrence data is quite common in many real applications. Latent Semantic Analysis (LSA) has been successfully used to identify semantic relations in such data. However, LSA c...
Xuanhui Wang, Jian-Tao Sun, Zheng Chen, ChengXiang...
CAV
2009
Springer
133views Hardware» more  CAV 2009»
14 years 10 months ago
Cardinality Abstraction for Declarative Networking Applications
ity Abstraction for Declarative Networking Applications Juan A. Navarro P?erez, Andrey Rybalchenko, and Atul Singh Max Planck Institute for Software Systems (MPI-SWS) Declarative N...
Andrey Rybalchenko, Atul Singh, Juan Antonio Navar...