Jonathan L. Shapiro

37 papers A 9B 1C 1Journal 10Unranked 14

Year	Rank	Type	Title / Venue / Authors
2021	J	`jnl`	Machine Learning-Based Soft Sensors for Vacuum Distillation Unit. CoRR Kamil Oster, Stefan Güttel, Lu Chen, Jonathan L. Shapiro, Megan Jobson
2021	J	`jnl`	Pre-treatment of outliers and anomalies in plant data: Methodology and case study of a Vacuum Distillation Unit. CoRR Kamil Oster, Stefan Güttel, Jonathan L. Shapiro, Lu Chen, Megan Jobson
2020	J	`jnl`	Eliminating Catastrophic Interference with Biased Competition. CoRR Amelia Elizabeth Pollard, Jonathan L. Shapiro
2020	J	`jnl`	Visual Question Answering as a Multi-Task Problem. CoRR Amelia Elizabeth Pollard, Jonathan L. Shapiro
2018	C	`conf`	A Bayesian Approach to Dealing with Device Heterogeneity in an Indoor Positioning System. IPIN Kyle F. Davies, Ian G. Jones, Jonathan L. Shapiro
2017	J	`jnl`	Opponent Modeling by Expectation-Maximization and Sequence Prediction in Simplified Poker. IEEE Trans. Comput. Intell. AI Games Richard Mealing, Jonathan L. Shapiro
2015	A	`conf`	Convergence of Strategies in Simple Co-Adapting Games. FOGA Richard Mealing, Jonathan L. Shapiro
2015	—	`conf`	Detecting and reducing redundancy in alarm networks. CASE Timothy D. Butters, Stefan Güttel, Jonathan L. Shapiro
2013	—	`conf`	Opponent Modelling by Sequence Prediction and Lookahead in Two-Player Games. ICAISC (2) Richard Mealing, Jonathan L. Shapiro
2013	J	`jnl`	Theory of Evolutionary Algorithms (Dagstuhl Seminar 13271). Dagstuhl Reports Benjamin Doerr, Nikolaus Hansen, Jonathan L. Shapiro, L. Darrell Whitley
2010	—	`conf`	10361 Abstracts Collection and Executive Summary - Theory of Evolutionary Algorithms. Theory of Evolutionary Algorithms Anne Auger, Jonathan L. Shapiro, L. Darrell Whitley, Carsten Witt
2010	—	`ed.`	Theory of Evolutionary Algorithms, 05.09. - 10.09.2010 Theory of Evolutionary Algorithms Anne Auger, Jonathan L. Shapiro, L. Darrell Whitley, Carsten Witt
2009	—	`conf`	Modeling Failure Propagation in Large-Scale Engineering Networks. Complex (2) Markus Schläpfer, Jonathan L. Shapiro
2009	A	`conf`	Stability of learning dynamics in two-agent, imperfect-information games. FOGA John Michael Butterworth, Jonathan L. Shapiro
2007	A	`conf`	Addressing sampling errors and diversity loss in UMDA. GECCO Jürgen Branke, Clemens Lode, Jonathan L. Shapiro
2007	A	`conf`	Parameter cross-validation and early-stopping in univariate marginal distribution algorithm. GECCO Hao Wu, Jonathan L. Shapiro
2007	J	`jnl`	Sparse Distributed Memory Using Rank-Order Neural Codes. IEEE Trans. Neural Networks Stephen B. Furber, Gavin Brown, Joy Bose, J. Mike Cumpstey, P. Marshall, Jonathan L. Shapiro
2006	J	`jnl`	An associative memory for the on-line recognition and prediction of temporal sequences CoRR Joy Bose, Stephen B. Furber, Jonathan L. Shapiro
2006	A	`conf`	Diversity Loss in General Estimation of Distribution Algorithms. PPSN Jonathan L. Shapiro
2006	A	`conf`	Does overfitting affect performance in estimation of distribution algorithms. GECCO Hao Wu, Jonathan L. Shapiro
2006	A	`conf`	Model Complexity vs. Performance in the Bayesian Optimization Algorithm. PPSN Elon Santos Correa, Jonathan L. Shapiro
2005	—	`conf`	A Spiking Neural Sparse Distributed Memory Implementation for Learning and Predicting Temporal Sequences. ICANN (1) Joy Bose, Stephen B. Furber, Jonathan L. Shapiro
2005	—	`conf`	A System for Transmitting a Coherent Burst of Activity Through a Network of Spiking Neurons. WIRN/NAIS Joy Bose, Stephen B. Furber, Jonathan L. Shapiro
2005	B	`conf`	An associative memory for the on-line recognition and prediction of temporal sequences. IJCNN Joy Bose, Steve B. Furber, Jonathan L. Shapiro
2005	—	`conf`	Choosing Search Algorithms in Bayesian Optimization Algorithm. IEC (Prague) Hao Wu, Jonathan L. Shapiro
2005	J	`jnl`	Drift and Scaling in Estimation of Distribution Algorithms. Evol. Comput. Jonathan L. Shapiro
2002	—	`conf`	Scaling of Probability-Based Optimization Algorithms. NIPS Jonathan L. Shapiro
2002	A	`conf`	The Sensitivity of PBIL to Its Learning Rate, and How Detailed Balance Can Remove It. FOGA Jonathan L. Shapiro
2001	—	`conf`	Genetic Algorithms in Machine Learning. Machine Learning and Its Applications Jonathan L. Shapiro
2001	—	`conf`	Reinforcement Learning and Time Perception -- a Model of Animal Experiments. NIPS Jonathan L. Shapiro, John Wearden
2001	—	`conf`	The Importance of Selection Mechanisms in Distribution Estimation Algorithms. Artificial Evolution Andrew Johnson, Jonathan L. Shapiro
2000	—	`conf`	A Simple Model Exhibiting Scalar Timing. NCPW Jonathan L. Shapiro, John Wearden, Rossano Barone
1998	A	`conf`	Does Data-Model Co-evolution Improve Generalization Performance of Evolving Learners? PPSN Jonathan L. Shapiro
1997	—	`ed.`	Evolutionary Computing, AISB International Workshop, Manchester, UK, April 7-8, 1997, Selected Papers Evolutionary Computing, AISB Workshop David Corne, Jonathan L. Shapiro
1997	J	`jnl`	Use of an Artificial Neural Network in Estimating Prevalence and Assessing Underdiagnisis of Asthma. Neural Comput. Appl. Sybil Hirsch, Jonathan L. Shapiro, Peter I. Frank
1995	—	`conf`	Maximum Entropy Analysis of Genetic Algorithm Operators. Evolutionary Computing, AISB Workshop Jonathan L. Shapiro, Adam Prügel-Bennett
1993	—	`conf`	Non-Linear Statistical Analysis and Self-Organizing Hebbian Networks. NIPS Jonathan L. Shapiro, Adam Prügel-Bennett