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TIP
2010
127views more  TIP 2010»
14 years 8 months ago
Bayesian Compressive Sensing Using Laplace Priors
In this paper we model the components of the compressive sensing (CS) problem, i.e., the signal acquisition process, the unknown signal coefficients and the model parameters for ...
S. Derin Babacan, Rafael Molina, Aggelos K. Katsag...
ICIP
1997
IEEE
15 years 11 months ago
Feature-Oriented Rate Shaping of Pre-Compressed Image/Video
Rate shaping plays an important role in transmitting compressed video on a network with dynamic bandwidth. In this paper, we present a scheme for rate shaping JPEG/MPEG-precompres...
Wenjun Zeng, Baining Guo, Bede Liu
AGILEDC
2006
IEEE
15 years 4 months ago
What Lessons Can the Agile Community Learn from A Maverick Fighter Pilot?
For the agile software development community, agility is defined by the values expressed in the agile manifesto. But in concrete terms, what does it mean for a software project to...
Steve Adolph
NEUROSCIENCE
2001
Springer
15 years 2 months ago
Analysis and Synthesis of Agents That Learn from Distributed Dynamic Data Sources
We propose a theoretical framework for specification and analysis of a class of learning problems that arise in open-ended environments that contain multiple, distributed, dynamic...
Doina Caragea, Adrian Silvescu, Vasant Honavar
GECCO
2009
Springer
134views Optimization» more  GECCO 2009»
15 years 2 months ago
Estimating the distribution and propagation of genetic programming building blocks through tree compression
Shin et al [19] and McKay et al [15] previously applied tree compression and semantics-based simplification to study the distribution of building blocks in evolving Genetic Progr...
Robert I. McKay, Xuan Hoai Nguyen, James R. Cheney...