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ACML
2009
Springer
15 years 9 months ago
Learning Algorithms for Domain Adaptation
A fundamental assumption for any machine learning task is to have training and test data instances drawn from the same distribution while having a sufficiently large number of tra...
Manas A. Pathak, Eric Nyberg
GECCO
2006
Springer
181views Optimization» more  GECCO 2006»
15 years 8 months ago
Particle swarm with speciation and adaptation in a dynamic environment
This paper describes an extension to a speciation-based particle swarm optimizer (SPSO) to improve performance in dynamic environments. The improved SPSO has adopted several prove...
Xiaodong Li, Jürgen Branke, Tim Blackwell
JCP
2008
126views more  JCP 2008»
15 years 4 months ago
Hardware/Software Co-design Approach for an ADALINE Based Adaptive Control System
Abstract--In this paper, we report some results on hardware and software co-design of an adaptive linear neuron (ADALINE) based control system. A discrete-time Proportional-Integra...
Shouling He, Xuping Xu
TIP
2008
154views more  TIP 2008»
15 years 4 months ago
Adaptive Local Linear Regression With Application to Printer Color Management
Abstract--Local learning methods, such as local linear regression and nearest neighbor classifiers, base estimates on nearby training samples, neighbors. Usually, the number of nei...
Maya R. Gupta, Eric K. Garcia, E. Chin
TNN
2008
132views more  TNN 2008»
15 years 4 months ago
Just-in-Time Adaptive Classifiers - Part I: Detecting Nonstationary Changes
Abstract--The stationarity requirement for the process generating the data is a common assumption in classifiers' design. When such hypothesis does not hold, e.g., in applicat...
Cesare Alippi, Manuel Roveri