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» Controlling Model Complexity in Flow Estimation
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GECCO
2007
Springer
155views Optimization» more  GECCO 2007»
14 years 2 months ago
Solving the MAXSAT problem using a multivariate EDA based on Markov networks
Markov Networks (also known as Markov Random Fields) have been proposed as a new approach to probabilistic modelling in Estimation of Distribution Algorithms (EDAs). An EDA employ...
Alexander E. I. Brownlee, John A. W. McCall, Deryc...
ICRA
2009
IEEE
111views Robotics» more  ICRA 2009»
14 years 3 months ago
Model-based and model-free reinforcement learning for visual servoing
— To address the difficulty of designing a controller for complex visual-servoing tasks, two learning-based uncalibrated approaches are introduced. The first method starts by b...
Amir Massoud Farahmand, Azad Shademan, Martin J&au...
SIGCOMM
2012
ACM
11 years 11 months ago
Abstractions for network update
ions for Network Update Mark Reitblatt Cornell Nate Foster Cornell Jennifer Rexford Princeton Cole Schlesinger Princeton David Walker Princeton Configuration changes are a common...
Mark Reitblatt, Nate Foster, Jennifer Rexford, Col...
WSC
2004
13 years 9 months ago
On Using Monte Carlo Methods for Scheduling
Monte Carlo techniques have long been used (since Buffon's experiment to approximate the value of by tossing a needle onto striped paper) to analyze phenomena which, due to ...
Samarn Chantaravarapan, Ali K. Gunal, Edward J. Wi...
SAC
2003
ACM
14 years 1 months ago
TinyGALS: A Programming Model for Event-Driven Embedded Systems
Networked embedded systems such as wireless sensor networks are usually designed to be event-driven so that they are reactive and power efficient. Programming embedded systems wit...
Elaine Cheong, Judith Liebman, Jie Liu, Feng Zhao