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ICCV
2009
IEEE
15 years 3 months ago
Learning Pedestrian Dynamics from the Real World
In this paper we describe a method to learn parameters which govern pedestrian motion by observing video data. Our learning framework is based on variational mode learning and a...
Paul Scovanner, Marshall Tappen
CEC
2005
IEEE
14 years 7 days ago
A note on the population based incremental learning with infinite population size
In this paper, we study the dynamical properties of the population based incremental learning (PBIL) algorithm when it uses truncation, proportional, and Boltzmann selection schema...
Reza Rastegar, Mohammad Reza Meybodi
WECWIS
2009
IEEE
162views ECommerce» more  WECWIS 2009»
14 years 5 months ago
QoS-Driven Web Service Composition Using Learning-Based Depth First Search
—The goal of the Web Service Composition (WSC) problem is to find an optimal composition of web services to satisfy a given request using their syntactic and/or semantic feature...
Wonhong Nam, Hyunyoung Kil, Jungjae Lee
AAMAS
2007
Springer
13 years 10 months ago
Parallel Reinforcement Learning with Linear Function Approximation
In this paper, we investigate the use of parallelization in reinforcement learning (RL), with the goal of learning optimal policies for single-agent RL problems more quickly by us...
Matthew Grounds, Daniel Kudenko
CVPR
2009
IEEE
15 years 5 months ago
Let the Kernel Figure it Out; Principled Learning of Pre-processing for Kernel Classifiers
Most modern computer vision systems for high-level tasks, such as image classification, object recognition and segmentation, are based on learning algorithms that are able to se...
Peter V. Gehler, Sebastian Nowozin