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» Algorithmic randomness of continuous functions
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JSAC
1998
126views more  JSAC 1998»
13 years 8 months ago
Iterative Decoding of Compound Codes by Probability Propagation in Graphical Models
Abstract—We present a unified graphical model framework for describing compound codes and deriving iterative decoding algorithms. After reviewing a variety of graphical models (...
Frank R. Kschischang, Brendan J. Frey
FOCS
2008
IEEE
14 years 3 months ago
What Can We Learn Privately?
Learning problems form an important category of computational tasks that generalizes many of the computations researchers apply to large real-life data sets. We ask: what concept ...
Shiva Prasad Kasiviswanathan, Homin K. Lee, Kobbi ...
CVPR
2005
IEEE
14 years 11 months ago
Digital Tapestry
This paper addresses the novel problem of automatically synthesizing an output image from a large collection of different input images. The synthesized image, called a digital tap...
Carsten Rother, Sanjiv Kumar, Vladimir Kolmogorov,...
GECCO
2006
Springer
133views Optimization» more  GECCO 2006»
14 years 15 days ago
Selecting for evolvable representations
Evolutionary algorithms tend to produce solutions that are not evolvable: Although current fitness may be high, further search is impeded as the effects of mutation and crossover ...
Joseph Reisinger, Risto Miikkulainen
APPROX
2005
Springer
111views Algorithms» more  APPROX 2005»
14 years 2 months ago
Sampling Bounds for Stochastic Optimization
A large class of stochastic optimization problems can be modeled as minimizing an objective function f that depends on a choice of a vector x ∈ X, as well as on a random external...
Moses Charikar, Chandra Chekuri, Martin Pál