Jonathan L. Shapiro

Publication Activity (10 Years)

Years Active: 1993-2021
Publications (10 Years): 8

Top Topics

Sequence Prediction

Opponent Modeling

Top Venues

Publications

Kamil Oster, Stefan Güttel, Jonathan L. Shapiro, Lu Chen, Megan Jobson
Pre-treatment of outliers and anomalies in plant data: Methodology and case study of a Vacuum Distillation Unit. CoRR (2021)
Kamil Oster, Stefan Güttel, Lu Chen, Jonathan L. Shapiro, Megan Jobson
Machine Learning-Based Soft Sensors for Vacuum Distillation Unit. CoRR (2021)
Amelia Elizabeth Pollard, Jonathan L. Shapiro
Eliminating Catastrophic Interference with Biased Competition. CoRR (2020)
Amelia Elizabeth Pollard, Jonathan L. Shapiro
Visual Question Answering as a Multi-Task Problem. CoRR (2020)
Kyle F. Davies, Ian G. Jones, Jonathan L. Shapiro
A Bayesian Approach to Dealing with Device Heterogeneity in an Indoor Positioning System. IPIN (2018)
Richard Mealing, Jonathan L. Shapiro
Opponent Modeling by Expectation-Maximization and Sequence Prediction in Simplified Poker. IEEE Trans. Comput. Intell. AI Games 9 (1) (2017)
Richard Mealing, Jonathan L. Shapiro
Convergence of Strategies in Simple Co-Adapting Games. FOGA (2015)
Timothy D. Butters, Stefan Güttel, Jonathan L. Shapiro
Detecting and reducing redundancy in alarm networks. CASE (2015)
Benjamin Doerr, Nikolaus Hansen, Jonathan L. Shapiro, L. Darrell Whitley
Theory of Evolutionary Algorithms (Dagstuhl Seminar 13271). Dagstuhl Reports 3 (7) (2013)
Richard Mealing, Jonathan L. Shapiro
Opponent Modelling by Sequence Prediction and Lookahead in Two-Player Games. ICAISC (2) (2013)
Anne Auger, Jonathan L. Shapiro, L. Darrell Whitley, Carsten Witt
10361 Abstracts Collection and Executive Summary - Theory of Evolutionary Algorithms. Theory of Evolutionary Algorithms (2010)
John Michael Butterworth, Jonathan L. Shapiro
Stability of learning dynamics in two-agent, imperfect-information games. FOGA (2009)
Markus Schläpfer, Jonathan L. Shapiro
Modeling Failure Propagation in Large-Scale Engineering Networks. Complex (2) (2009)
Jürgen Branke, Clemens Lode, Jonathan L. Shapiro
Addressing sampling errors and diversity loss in UMDA. GECCO (2007)
Hao Wu, Jonathan L. Shapiro
Parameter cross-validation and early-stopping in univariate marginal distribution algorithm. GECCO (2007)
Stephen B. Furber, Gavin Brown, Joy Bose, J. Mike Cumpstey, P. Marshall, Jonathan L. Shapiro
Sparse Distributed Memory Using Rank-Order Neural Codes. IEEE Trans. Neural Networks 18 (3) (2007)
Jonathan L. Shapiro
Diversity Loss in General Estimation of Distribution Algorithms. PPSN (2006)
Elon Santos Correa, Jonathan L. Shapiro
Model Complexity vs. Performance in the Bayesian Optimization Algorithm. PPSN (2006)
Hao Wu, Jonathan L. Shapiro
Does overfitting affect performance in estimation of distribution algorithms. GECCO (2006)
Joy Bose, Stephen B. Furber, Jonathan L. Shapiro
An associative memory for the on-line recognition and prediction of temporal sequences CoRR (2006)
Joy Bose, Stephen B. Furber, Jonathan L. Shapiro
A System for Transmitting a Coherent Burst of Activity Through a Network of Spiking Neurons. WIRN/NAIS (2005)
Jonathan L. Shapiro
Drift and Scaling in Estimation of Distribution Algorithms. Evol. Comput. 13 (1) (2005)
Hao Wu, Jonathan L. Shapiro
Choosing Search Algorithms in Bayesian Optimization Algorithm. IEC (Prague) (2005)
Joy Bose, Stephen B. Furber, Jonathan L. Shapiro
A Spiking Neural Sparse Distributed Memory Implementation for Learning and Predicting Temporal Sequences. ICANN (1) (2005)
Jonathan L. Shapiro
Scaling of Probability-Based Optimization Algorithms. NIPS (2002)
Jonathan L. Shapiro
The Sensitivity of PBIL to Its Learning Rate, and How Detailed Balance Can Remove It. FOGA (2002)
Andrew Johnson, Jonathan L. Shapiro
The Importance of Selection Mechanisms in Distribution Estimation Algorithms. Artificial Evolution (2001)
Jonathan L. Shapiro
Genetic Algorithms in Machine Learning. Machine Learning and Its Applications (2001)
Jonathan L. Shapiro, John Wearden
Reinforcement Learning and Time Perception -- a Model of Animal Experiments. NIPS (2001)
Jonathan L. Shapiro, John Wearden, Rossano Barone
A Simple Model Exhibiting Scalar Timing. NCPW (2000)
Jonathan L. Shapiro
Does Data-Model Co-evolution Improve Generalization Performance of Evolving Learners? PPSN (1998)
Sybil Hirsch, Jonathan L. Shapiro, Peter I. Frank
Use of an Artificial Neural Network in Estimating Prevalence and Assessing Underdiagnisis of Asthma. Neural Comput. Appl. 5 (2) (1997)
Jonathan L. Shapiro, Adam Prügel-Bennett
Maximum Entropy Analysis of Genetic Algorithm Operators. Evolutionary Computing, AISB Workshop (1995)
Jonathan L. Shapiro, Adam Prügel-Bennett
Non-Linear Statistical Analysis and Self-Organizing Hebbian Networks. NIPS (1993)