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ICIP
2006
IEEE
15 years 3 months ago
Compressive Sampling Vs. Conventional Imaging
Compressive sampling (CS), or “Compressed Sensing,” has recently generated a tremendous amount of excitement in the image processing community. CS involves taking a relatively...
Jarvis Haupt, Robert Nowak
NIPS
2008
14 years 11 months ago
Sparse Signal Recovery Using Markov Random Fields
Compressive Sensing (CS) combines sampling and compression into a single subNyquist linear measurement process for sparse and compressible signals. In this paper, we extend the th...
Volkan Cevher, Marco F. Duarte, Chinmay Hegde, Ric...
IPSN
2003
Springer
15 years 3 months ago
Beyond Average: Toward Sophisticated Sensing with Queries
High-level query languages are an attractive interface for sensor networks, potentially relieving application programmers from the burdens of distributed, embedded programming. In ...
Joseph M. Hellerstein, Wei Hong, Samuel Madden, Ky...
KES
2008
Springer
14 years 9 months ago
Driven by Compression Progress
I argue that data becomes temporarily interesting by itself to some self-improving, but computationally limited, subjective observer once he learns to predict or compress the data...
Jürgen Schmidhuber
CORR
2010
Springer
200views Education» more  CORR 2010»
14 years 10 months ago
Unified Compression-Based Acceleration of Edit-Distance Computation
The edit distance problem is a classical fundamental problem in computer science in general, and in combinatorial pattern matching in particular. The standard dynamic programming s...
Danny Hermelin, Gad M. Landau, Shir Landau, Oren W...