Jonathan L. Shapiro - researchr alias

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Viewing Publication 1 - 29 from 29

2018

A Bayesian Approach to Dealing with Device Heterogeneity in an Indoor Positioning SystemKyle F. Davies, Ian G. Jones, Jonathan L. Shapiro. ipin 2018: 1-8 [doi]

2017

Opponent Modeling by Expectation-Maximization and Sequence Prediction in Simplified PokerRichard Mealing, Jonathan L. Shapiro. tciaig, 9(1):11-24, 2017. [doi]

2015

Detecting and reducing redundancy in alarm networksTimothy D. Butters, Stefan Guttel, Jonathan L. Shapiro. case 2015: 1224-1229 [doi]

Convergence of Strategies in Simple Co-Adapting GamesRichard Mealing, Jonathan L. Shapiro. foga 2015: 176-190 [doi]

2013

Theory of Evolutionary Algorithms (Dagstuhl Seminar 13271)Benjamin Doerr, Nikolaus Hansen, Jonathan L. Shapiro, L. Darrell Whitley. dagstuhl-reports, 3(7):1-28, 2013. [doi]

Opponent Modelling by Sequence Prediction and Lookahead in Two-Player GamesRichard Mealing, Jonathan L. Shapiro. icaisc 2013: 385-396 [doi]

2010

10361 Abstracts Collection and Executive Summary - Theory of Evolutionary AlgorithmsAnne Auger, Jonathan L. Shapiro, L. Darrell Whitley, Carsten Witt. Dagstuhl 2010: [doi]

2009

Stability of learning dynamics in two-agent, imperfect-information gamesJohn M. Butterworth, Jonathan L. Shapiro. foga 2009: 131-140 [doi]

Modeling Failure Propagation in Large-Scale Engineering NetworksMarkus Schläpfer, Jonathan L. Shapiro. bertinoro 2009: 2127-2138 [doi]

2007

2006

Model Complexity vs. Performance in the Bayesian Optimization AlgorithmElon S. Correa, Jonathan L. Shapiro. ppsn 2006: 998-1007 [doi]

Diversity Loss in General Estimation of Distribution AlgorithmsJonathan L. Shapiro. ppsn 2006: 92-101 [doi]

Does overfitting affect performance in estimation of distribution algorithmsHao Wu, Jonathan L. Shapiro. gecco 2006: 433-434 [doi]

2005

2002

Scaling of Probability-Based Optimization AlgorithmsJonathan L. Shapiro. nips 2003: 383-390 [doi]

The Sensitivity of PBIL to Its Learning Rate, and How Detailed Balance Can Remove ItJonathan L. Shapiro. foga 2003: 115-132

2001

The Importance of Selection Mechanisms in Distribution Estimation AlgorithmsAndrew Johnson, Jonathan L. Shapiro. ae 2002: 91-103 [doi]

Genetic Algorithms in Machine LearningJonathan L. Shapiro. ac 2001: 146-168 [doi]

Reinforcement Learning and Time Perception -- a Model of Animal ExperimentsJonathan L. Shapiro, J. Wearden. nips 2001: 115-122 [doi]

2000

A Simple Model Exhibiting Scalar TimingJonathan L. Shapiro, John Wearden, Rossano Barone. ncpw 2001: 43-52 [doi]

1998

Does Data-Model Co-evolution Improve Generalization Performance of Evolving Learners?Jonathan L. Shapiro. ppsn 1998: 540-549 [doi]

1997

Use of an Artificial Neural Network in Estimating Prevalence and Assessing Underdiagnisis of AsthmaSybil Hirsch, Jonathan L. Shapiro, Peter I. Frank. nca, 5(2):124-128, 1997.

1995

Maximum Entropy Analysis of Genetic Algorithm OperatorsJonathan L. Shapiro, Adam Prügel-Bennett. aisb 1995: 14-24

1993

Non-Linear Statistical Analysis and Self-Organizing Hebbian NetworksJonathan L. Shapiro, Adam Prügel-Bennett. nips 1994: 407-414 [doi]

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