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ORCIDJonathan L. Shapiro
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- affiliation: University of Manchester, UK
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2020 – today
- 2021
[i12]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 abs/2106.14641 (2021)- [i11]Kamil Oster, Stefan Güttel, Lu Chen, Jonathan L. Shapiro, Megan Jobson:
Machine Learning-Based Soft Sensors for Vacuum Distillation Unit. CoRR abs/2111.11251 (2021) - 2020
- [i10]Amelia Elizabeth Pollard, Jonathan L. Shapiro:
Visual Question Answering as a Multi-Task Problem. CoRR abs/2007.01780 (2020) - [i9]Amelia Elizabeth Pollard, Jonathan L. Shapiro:
Eliminating Catastrophic Interference with Biased Competition. CoRR abs/2007.02833 (2020)
2010 – 2019
- 2018
- [c36]Kyle F. Davies, Ian G. Jones, Jonathan L. Shapiro:
A Bayesian Approach to Dealing with Device Heterogeneity in an Indoor Positioning System. IPIN 2018: 1-8 - 2017
- [j8]Richard Mealing, Jonathan L. Shapiro:
Opponent Modeling by Expectation-Maximization and Sequence Prediction in Simplified Poker. IEEE Trans. Comput. Intell. AI Games 9(1): 11-24 (2017) - 2015
- [c35]Timothy D. Butters, Stefan Güttel
, Jonathan L. Shapiro:
Detecting and reducing redundancy in alarm networks. CASE 2015: 1224-1229 - [c34]Adam Prügel-Bennett, Jonathan E. Rowe, Jonathan Shapiro:
Run-Time Analysis of Population-Based Evolutionary Algorithm in Noisy Environments. FOGA 2015: 69-75 - [c33]Richard Mealing, Jonathan L. Shapiro:
Convergence of Strategies in Simple Co-Adapting Games. FOGA 2015: 176-190 - 2013
- [j7]Tim Robinson, Thomas Cronin, Haider Ibrahim, Mark Jinks, Timothy Molitor, Joshua Newman, Jonathan Shapiro:
Smartphone Use and Acceptability Among Clinical Medical Students: A Questionnaire-Based Study. J. Medical Syst. 37(3): 9936 (2013) - [c32]Joseph Charles Mellor, Jonathan Shapiro:
Thompson Sampling in Switching Environments with Bayesian Online Change Detection. AISTATS 2013: 442-450 - [c31]Richard Mealing, Jonathan L. Shapiro:
Opponent Modelling by Sequence Prediction and Lookahead in Two-Player Games. ICAISC (2) 2013: 385-396 - [i8]Joseph Charles Mellor, Jonathan Shapiro:
Thompson Sampling in Switching Environments with Bayesian Online Change Point Detection. CoRR abs/1302.3721 (2013) - [i7]Benjamin Doerr, Nikolaus Hansen, Jonathan L. Shapiro, L. Darrell Whitley:
Theory of Evolutionary Algorithms (Dagstuhl Seminar 13271). Dagstuhl Reports 3(7): 1-28 (2013) - 2012
- [i6]Ruefei He, Jonathan Shapiro:
Bayesian Mixture Models for Frequent Itemset Discovery. CoRR abs/1209.6001 (2012) - 2010
- [e2]Anne Auger, Jonathan L. Shapiro, L. Darrell Whitley, Carsten Witt:
Theory of Evolutionary Algorithms, 05.09. - 10.09.2010. Dagstuhl Seminar Proceedings 10361, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, Germany 2010 [contents] - [i5]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
2000 – 2009
- 2009
- [c30]Markus Schläpfer, Jonathan L. Shapiro:
Modeling Failure Propagation in Large-Scale Engineering Networks. Complex (2) 2009: 2127-2138 - [c29]John Michael Butterworth, Jonathan L. Shapiro:
Stability of learning dynamics in two-agent, imperfect-information games. FOGA 2009: 131-140 - 2007
- [j6]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): 648-659 (2007) - [c28]Jürgen Branke, Clemens Lode, Jonathan L. Shapiro:
Addressing sampling errors and diversity loss in UMDA. GECCO 2007: 508-515 - [c27]Hao Wu, Jonathan L. Shapiro:
Parameter cross-validation and early-stopping in univariate marginal distribution algorithm. GECCO 2007: 632-633 - [c26]Chong Liu, Jonathan Shapiro:
Implementing Classical Conditioning with Spiking Neurons. ICANN (1) 2007: 400-410 - 2006
- [c25]Jonathan Shapiro:
Programming language challenges in systems codes: why systems programmers still use C, and what to do about it. PLOS 2006: 9 - [c24]Hao Wu, Jonathan L. Shapiro:
Does overfitting affect performance in estimation of distribution algorithms. GECCO 2006: 433-434 - [c23]Jonathan L. Shapiro:
Diversity Loss in General Estimation of Distribution Algorithms. PPSN 2006: 92-101 - [c22]Elon Santos Correa, Jonathan L. Shapiro:
Model Complexity vs. Performance in the Bayesian Optimization Algorithm. PPSN 2006: 998-1007 - [i4]Joy Bose, Stephen B. Furber, Jonathan L. Shapiro:
An associative memory for the on-line recognition and prediction of temporal sequences. CoRR abs/cs/0611020 (2006) - 2005
- [j5]Jonathan L. Shapiro:
Drift and Scaling in Estimation of Distribution Algorithms. Evol. Comput. 13(1): 99-123 (2005) - [j4]Stephen Marsland, Ulrich Nehmzow, Jonathan Shapiro:
On-line novelty detection for autonomous mobile robots. Robotics Auton. Syst. 51(2-3): 191-206 (2005) - [c21]Joy Bose, Stephen B. Furber, Jonathan L. Shapiro:
A Spiking Neural Sparse Distributed Memory Implementation for Learning and Predicting Temporal Sequences. ICANN (1) 2005: 115-120 - [c20]Joy Bose, Steve B. Furber, Jonathan L. Shapiro:
An associative memory for the on-line recognition and prediction of temporal sequences. IJCNN 2005: 1223-1228 - [c19]Hao Wu, Jonathan L. Shapiro:
Choosing Search Algorithms in Bayesian Optimization Algorithm. IEC (Prague) 2005: 51-55 - [c18]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: 44-48 - 2003
- [c17]Jason Fleischer, Stephen Marsland, Jonathan Shapiro:
Sensory Anticipation for Autonomous Selection of Robot Landmarks. ABiALS 2003: 201-221 - 2002
- [j3]Tom Duckett, Stephen Marsland, Jonathan Shapiro:
Fast, On-Line Learning of Globally Consistent Maps. Auton. Robots 12(3): 287-300 (2002) - [j2]Stephen Marsland, Jonathan Shapiro, Ulrich Nehmzow:
A self-organising network that grows when required. Neural Networks 15(8-9): 1041-1058 (2002) - [c16]Jonathan L. Shapiro:
The Sensitivity of PBIL to Its Learning Rate, and How Detailed Balance Can Remove It. FOGA 2002: 115-132 - [c15]Jonathan L. Shapiro:
Scaling of Probability-Based Optimization Algorithms. NIPS 2002: 383-390 - 2001
- [c14]Jonathan L. Shapiro:
Genetic Algorithms in Machine Learning. Machine Learning and Its Applications 2001: 146-168 - [c13]Andrew Johnson, Jonathan L. Shapiro:
The Importance of Selection Mechanisms in Distribution Estimation Algorithms. Artificial Evolution 2001: 91-103 - [c12]Jonathan L. Shapiro, John Wearden:
Reinforcement Learning and Time Perception -- a Model of Animal Experiments. NIPS 2001: 115-122 - 2000
- [c11]Tom Duckett, Stephen Marsland, Jonathan Shapiro:
Learning Globally Consistent Maps by Relaxation. ICRA 2000: 3841-3846 - [c10]Jonathan L. Shapiro, John Wearden, Rossano Barone:
A Simple Model Exhibiting Scalar Timing. NCPW 2000: 43-52 - [i3]Stephen Marsland, Ulrich Nehmzow, Jonathan Shapiro:
Novelty Detection for Robot Neotaxis. CoRR cs.RO/0006005 (2000) - [i2]Stephen Marsland, Ulrich Nehmzow, Jonathan Shapiro:
A Real-Time Novelty Detector for a Mobile Robot. CoRR cs.RO/0006006 (2000) - [i1]Stephen Marsland, Ulrich Nehmzow, Jonathan Shapiro:
Novelty Detection on a Mobile Robot Using Habituation. CoRR cs.RO/0006007 (2000)
1990 – 1999
- 1998
- [c9]Jonathan L. Shapiro:
Does Data-Model Co-evolution Improve Generalization Performance of Evolving Learners? PPSN 1998: 540-549 - 1997
- [j1]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): 124-128 (1997) - [e1]David Corne, Jonathan L. Shapiro:
Evolutionary Computing, AISB International Workshop, Manchester, UK, April 7-8, 1997, Selected Papers. Lecture Notes in Computer Science 1305, Springer 1997, ISBN 3-540-63476-2 [contents] - 1996
- [c8]Jonathan Shapiro, Adam Prügel-Bennett:
Genetic Algorithm Dynamics in a Two-well Potential. FOGA 1996: 101-116 - [c7]Magnus Rattray, Jonathan Shapiro:
Noisy Fitness Evaluation in Genetic Algorithms and the Dynamics of Learning. FOGA 1996: 117-139 - 1995
- [c6]Jonathan L. Shapiro, Adam Prügel-Bennett:
Maximum Entropy Analysis of Genetic Algorithm Operators. Evolutionary Computing, AISB Workshop 1995: 14-24 - 1994
- [c5]Jonathan Shapiro, Adam Prügel-Bennett, Magnus Rattray:
A Statistical Mechanical Formulation of the Dynamics of Genetic Algorithms. Evolutionary Computing, AISB Workshop 1994: 17-27 - 1993
- [c4]Jonathan L. Shapiro, Adam Prügel-Bennett:
Non-Linear Statistical Analysis and Self-Organizing Hebbian Networks. NIPS 1993: 407-414 - 1990
- [c3]Jonathan Shapiro, Peter Mowforth:
Data Fusion in 3D Through Surface Tracking. IEA/AIE (Vol. 1) 1990: 163-168 - [c2]Peter Mowforth, Jonathan Shapiro:
3D Data fusion for a mobile robot. IROS 1990: 1015-1020 - [c1]Jonathan Shapiro, Zhengping Jin:
An Interactive Colour Line Recognition System for Seismic Section Digitisation. MVA 1990: 223-226
Coauthor Index
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