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» Algorithmic randomness of continuous functions
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AAAI
1997
14 years 11 months ago
Effective Bayesian Inference for Stochastic Programs
In this paper, we propose a stochastic version of a general purpose functional programming language as a method of modeling stochastic processes. The language contains random choi...
Daphne Koller, David A. McAllester, Avi Pfeffer
INFOCOM
1999
IEEE
15 years 2 months ago
The Window Distribution of Idealized TCP Congestion Avoidance with Variable Packet Loss
Abstract--This paper analyzes the stationary behavior of the TCP congestion window performing ideal congestion avoidance when the packet loss probability is not constant, but varie...
Archan Misra, Teunis J. Ott
GECCO
2003
Springer
109views Optimization» more  GECCO 2003»
15 years 3 months ago
Real Royal Road Functions for Constant Population Size
Evolutionary and genetic algorithms (EAs and GAs) are quite successful randomized function optimizers. This success is mainly based on the interaction of different operators like ...
Tobias Storch, Ingo Wegener
CORR
2011
Springer
192views Education» more  CORR 2011»
14 years 4 months ago
Distribution-Independent Evolvability of Linear Threshold Functions
Valiant’s (2007) model of evolvability models the evolutionary process of acquiring useful functionality as a restricted form of learning from random examples. Linear threshold ...
Vitaly Feldman
ECAI
2010
Springer
14 years 11 months ago
Bayesian Monte Carlo for the Global Optimization of Expensive Functions
In the last decades enormous advances have been made possible for modelling complex (physical) systems by mathematical equations and computer algorithms. To deal with very long run...
Perry Groot, Adriana Birlutiu, Tom Heskes