Jonathan L. Shapiro

According to our database, Jonathan L. Shapiro authored at least 55 papers between 1990 and 2021.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2021

Machine Learning-Based Soft Sensors for Vacuum Distillation Unit.

Kamil Oster, Stefan Güttel, Lu Chen, Jonathan L. Shapiro, Megan Jobson

CoRR, 2021

Pre-treatment of outliers and anomalies in plant data: Methodology and case study of a Vacuum Distillation Unit.

Kamil Oster, Stefan Güttel, Jonathan L. Shapiro, Lu Chen, Megan Jobson

CoRR, 2021

2020

Eliminating Catastrophic Interference with Biased Competition.

Amelia Elizabeth Pollard, Jonathan L. Shapiro

CoRR, 2020

Visual Question Answering as a Multi-Task Problem.

Amelia Elizabeth Pollard, Jonathan L. Shapiro

CoRR, 2020

2018

A Bayesian Approach to Dealing with Device Heterogeneity in an Indoor Positioning System.

Kyle F. Davies, Ian G. Jones, Jonathan L. Shapiro

Proceedings of the 2018 International Conference on Indoor Positioning and Indoor Navigation, 2018

2017

Opponent Modeling by Expectation-Maximization and Sequence Prediction in Simplified Poker.

Richard Mealing, Jonathan L. Shapiro

IEEE Trans. Comput. Intell. AI Games, 2017

2015

Run-Time Analysis of Population-Based Evolutionary Algorithm in Noisy Environments.

Adam Prügel-Bennett, Jonathan E. Rowe, Jonathan Shapiro

Proceedings of the 2015 ACM Conference on Foundations of Genetic Algorithms XIII, Aberystwyth, United Kingdom, January 17, 2015

Convergence of Strategies in Simple Co-Adapting Games.

Richard Mealing, Jonathan L. Shapiro

Proceedings of the 2015 ACM Conference on Foundations of Genetic Algorithms XIII, Aberystwyth, United Kingdom, January 17, 2015

Detecting and reducing redundancy in alarm networks.

Timothy D. Butters, Stefan Güttel, Jonathan L. Shapiro

Proceedings of the IEEE International Conference on Automation Science and Engineering, 2015

2013

Smartphone Use and Acceptability Among Clinical Medical Students: A Questionnaire-Based Study.

Tim Robinson, Thomas Cronin, Haider Ibrahim, Mark Jinks, Timothy Molitor, Joshua Newman, Jonathan Shapiro

J. Medical Syst., 2013

Theory of Evolutionary Algorithms (Dagstuhl Seminar 13271).

Benjamin Doerr, Nikolaus Hansen, Jonathan L. Shapiro, L. Darrell Whitley

Dagstuhl Reports, 2013

Thompson Sampling in Switching Environments with Bayesian Online Change Point Detection

Joseph Charles Mellor, Jonathan Shapiro

CoRR, 2013

Opponent Modelling by Sequence Prediction and Lookahead in Two-Player Games.

Richard Mealing, Jonathan L. Shapiro

Proceedings of the Artificial Intelligence and Soft Computing, 2013

Thompson Sampling in Switching Environments with Bayesian Online Change Detection.

Joseph Charles Mellor, Jonathan Shapiro

Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, 2013

2012

Bayesian Mixture Models for Frequent Itemset Discovery

Ruefei He, Jonathan Shapiro

CoRR, 2012

2010

10361 Abstracts Collection and Executive Summary - Theory of Evolutionary Algorithms.

Anne Auger, Jonathan L. Shapiro, L. Darrell Whitley, Carsten Witt

Proceedings of the Theory of Evolutionary Algorithms, 05.09. - 10.09.2010, 2010

2009

Stability of learning dynamics in two-agent, imperfect-information games.

John Michael Butterworth, Jonathan L. Shapiro

Proceedings of the Foundations of Genetic Algorithms, 2009

Modeling Failure Propagation in Large-Scale Engineering Networks.

Markus Schläpfer, Jonathan L. Shapiro

Proceedings of the Complex Sciences, 2009

2007

Sparse Distributed Memory Using Rank-Order Neural Codes.

Stephen B. Furber, Gavin Brown, Joy Bose, J. Mike Cumpstey, P. Marshall, Jonathan L. Shapiro

IEEE Trans. Neural Networks, 2007

Implementing Classical Conditioning with Spiking Neurons.

Chong Liu, Jonathan Shapiro

Proceedings of the Artificial Neural Networks, 2007

Parameter cross-validation and early-stopping in univariate marginal distribution algorithm.

Hao Wu, Jonathan L. Shapiro

Proceedings of the Genetic and Evolutionary Computation Conference, 2007

Addressing sampling errors and diversity loss in UMDA.

Jürgen Branke, Clemens Lode, Jonathan L. Shapiro

Proceedings of the Genetic and Evolutionary Computation Conference, 2007

2006

An associative memory for the on-line recognition and prediction of temporal sequences

Joy Bose, Stephen B. Furber, Jonathan L. Shapiro

CoRR, 2006

Diversity Loss in General Estimation of Distribution Algorithms.

Jonathan L. Shapiro

Proceedings of the Parallel Problem Solving from Nature, 2006

Model Complexity vs. Performance in the Bayesian Optimization Algorithm.

Elon Santos Correa, Jonathan L. Shapiro

Proceedings of the Parallel Problem Solving from Nature, 2006

Does overfitting affect performance in estimation of distribution algorithms.

Hao Wu, Jonathan L. Shapiro

Proceedings of the Genetic and Evolutionary Computation Conference, 2006

Programming language challenges in systems codes: why systems programmers still use C, and what to do about it.

Jonathan Shapiro

Proceedings of the 3rd Workshop on Programming Languages and Operating Systems: Linguistic Support for Modern Operating Systems, 2006

2005

On-line novelty detection for autonomous mobile robots.

Stephen Marsland, Ulrich Nehmzow, Jonathan Shapiro

Robotics Auton. Syst., 2005

Drift and Scaling in Estimation of Distribution Algorithms.

Jonathan L. Shapiro

Evol. Comput., 2005

A System for Transmitting a Coherent Burst of Activity Through a Network of Spiking Neurons.

Joy Bose, Stephen B. Furber, Jonathan L. Shapiro

Proceedings of the Neural Nets, 16th Italian Workshop on Neural Nets, 2005

Choosing Search Algorithms in Bayesian Optimization Algorithm.

Hao Wu, Jonathan L. Shapiro

Proceedings of the International Enformatika Conference, 2005

A Spiking Neural Sparse Distributed Memory Implementation for Learning and Predicting Temporal Sequences.

Joy Bose, Stephen B. Furber, Jonathan L. Shapiro

Proceedings of the Artificial Neural Networks: Biological Inspirations, 2005

2003

Sensory Anticipation for Autonomous Selection of Robot Landmarks.

Jason Fleischer, Stephen Marsland, Jonathan Shapiro

Proceedings of the Anticipatory Behavior in Adaptive Learning Systems, 2003

2002

A self-organising network that grows when required.

Stephen Marsland, Jonathan Shapiro, Ulrich Nehmzow

Neural Networks, 2002

Fast, On-Line Learning of Globally Consistent Maps.

Tom Duckett, Stephen Marsland, Jonathan Shapiro

Auton. Robots, 2002

Scaling of Probability-Based Optimization Algorithms.

Jonathan L. Shapiro

Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002

The Sensitivity of PBIL to Its Learning Rate, and How Detailed Balance Can Remove It.

Jonathan L. Shapiro

Proceedings of the Seventh Workshop on Foundations of Genetic Algorithms, 2002

2001

Reinforcement Learning and Time Perception -- a Model of Animal Experiments.

Jonathan L. Shapiro, John Wearden

Proceedings of the Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, 2001

The Importance of Selection Mechanisms in Distribution Estimation Algorithms.

Andrew Johnson, Jonathan L. Shapiro

Proceedings of the Artificial Evolution, 2001

Genetic Algorithms in Machine Learning.

Jonathan L. Shapiro

Proceedings of the Machine Learning and Its Applications, Advanced Lectures, 2001

2000

Novelty Detection on a Mobile Robot Using Habituation

Stephen Marsland, Ulrich Nehmzow, Jonathan Shapiro

CoRR, 2000

A Real-Time Novelty Detector for a Mobile Robot

Stephen Marsland, Ulrich Nehmzow, Jonathan Shapiro

CoRR, 2000

Novelty Detection for Robot Neotaxis

Stephen Marsland, Ulrich Nehmzow, Jonathan Shapiro

CoRR, 2000

A Simple Model Exhibiting Scalar Timing.

Jonathan L. Shapiro, John Wearden, Rossano Barone

Proceedings of the Connectionist Models of Learning, 2000

Learning Globally Consistent Maps by Relaxation.

Tom Duckett, Stephen Marsland, Jonathan Shapiro

Proceedings of the 2000 IEEE International Conference on Robotics and Automation, 2000

1998

Does Data-Model Co-evolution Improve Generalization Performance of Evolving Learners?

Jonathan L. Shapiro

Proceedings of the Parallel Problem Solving from Nature, 1998

1997

Use of an Artificial Neural Network in Estimating Prevalence and Assessing Underdiagnisis of Asthma.

Sybil Hirsch, Jonathan L. Shapiro, Peter I. Frank

Neural Comput. Appl., 1997

1996

Genetic Algorithm Dynamics in a Two-well Potential.

Jonathan Shapiro, Adam Prügel-Bennett

Proceedings of the 4th Workshop on Foundations of Genetic Algorithms. San Diego, 1996

Noisy Fitness Evaluation in Genetic Algorithms and the Dynamics of Learning.

Magnus Rattray, Jonathan Shapiro

Proceedings of the 4th Workshop on Foundations of Genetic Algorithms. San Diego, 1996

1995

Maximum Entropy Analysis of Genetic Algorithm Operators.

Jonathan L. Shapiro, Adam Prügel-Bennett

Proceedings of the Evolutionary Computing, 1995

1994

A Statistical Mechanical Formulation of the Dynamics of Genetic Algorithms.

Jonathan Shapiro, Adam Prügel-Bennett, Magnus Rattray

Proceedings of the Evolutionary Computing, 1994

1993

Non-Linear Statistical Analysis and Self-Organizing Hebbian Networks.

Jonathan L. Shapiro, Adam Prügel-Bennett

Proceedings of the Advances in Neural Information Processing Systems 6, 1993

1990

An Interactive Colour Line Recognition System for Seismic Section Digitisation.

Jonathan Shapiro, Zhengping Jin

Proceedings of IAPR Workshop on Machine Vision Applications, 1990

3D Data fusion for a mobile robot.

Peter Mowforth, Jonathan Shapiro

Proceedings of the IEEE International Workshop on Intelligent Robots and Systems '90, 1990

Data Fusion in 3D Through Surface Tracking.

Jonathan Shapiro, Peter Mowforth

Proceedings of the Third International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, IEA/AIE 1990, July 15-18, 1990, The Mills House Hotel, Charleston, SC, USA, 1990