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Jonathan E. Fieldsend
Jonathan Edward Fieldsend
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- affiliation: University of Exeter, UK
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2020 – today
- 2024
- [j27]Xiangyu Yin, Wenjie Ruan
, Jonathan E. Fieldsend:
DIMBA: discretely masked black-box attack in single object tracking. Mach. Learn. 113(4): 1705-1723 (2024) - [j26]Jonathan E. Fieldsend
Introduction to the "Best of GECCO 2022" Special Issue: Part II. ACM Trans. Evol. Learn. Optim. 4(2): 6 (2024) - [c67]Ali Ahrari
New Tunable Test Problems for Benchmarking Niching Methods for Multimodal Optimization. GECCO 2024 - [c66]Ali Ahrari
Experimental Setup for GECCO 2024 Competition on Benchmarking Niching Methods for Multimodal Optimization. GECCO Companion 2024: 5-6 - [c65]Tianle Zhang, Yanghao Zhang, Ronghui Mu, Jiaxu Liu, Jonathan E. Fieldsend, Wenjie Ruan:
PRASS: Probabilistic Risk-averse Robust Learning with Stochastic Search. IJCAI 2024: 559-567 - 2023
- [j25]Gregory A. Daly
Data-driven plasma modelling: surrogate collisional radiative models of fluorocarbon plasmas from deep generative autoencoders. Mach. Learn. Sci. Technol. 4(3): 35035 (2023) - [j24]Jonathan E. Fieldsend
Editorial to the "Best of GECCO 2022" Special Issue: Part I. ACM Trans. Evol. Learn. Optim. 3(2): 4:1-4:2 (2023) - [c64]Arnaud Liefooghe
Feature-Based Benchmarking of Distance-Based Multi/Many-objective Optimisation Problems: A Machine Learning Perspective. EMO 2023: 260-273 - [c63]James Sakal
Genotype Diversity Measures for Escaping Plateau Regions in University Course Timetabling. GECCO Companion 2023: 2090-2098 - [c62]Melike D. Karatas, Marc Goodfellow, Jonathan E. Fieldsend:
Exploring the Uncertainty of Approximated Fitness Landscapes via Gaussian Process Realisations. SSCI 2023: 947-952 - [p9]Bekir Afsar
Many-Objective Quality Measures. Many-Criteria Optimization and Decision Analysis 2023: 113-148 - 2022
- [j23]Carina Ivascu, Richard M. Everson
Optimising Diversity in Classifier Ensembles. SN Comput. Sci. 3(3): 191 (2022) - [j22]Jonathan E. Fieldsend
A Visualizable Test Problem Generator for Many-Objective Optimization. IEEE Trans. Evol. Comput. 26(1): 1-11 (2022) - [c61]Jonathan E. Fieldsend
On the Active Use of an ND-Tree-Based Archive for Multi-Objective Optimisation. EA 2022: 1-14 - [c60]James Sakal
Towards a Many-Objective Optimiser for University Course Timetabling. EA 2022: 133-144 - [c59]Finley J. Gibson, Richard M. Everson, Jonathan E. Fieldsend:
Guiding surrogate-assisted multi-objective optimisation with decision maker preferences. GECCO 2022: 786-795 - [c58]Tianle Zhang
PRoA: A Probabilistic Robustness Assessment Against Functional Perturbations. ECML/PKDD (3) 2022: 154-170 - [c57]Alma A. M. Rahat
Efficient Approximation of Expected Hypervolume Improvement Using Gauss-Hermite Quadrature. PPSN (1) 2022: 90-103 - [e3]Jonathan E. Fieldsend, Markus Wagner:
GECCO '22: Genetic and Evolutionary Computation Conference, Boston, Massachusetts, USA, July 9 - 13, 2022. ACM 2022, ISBN 978-1-4503-9237-2 [contents] - [e2]Jonathan E. Fieldsend, Markus Wagner:
GECCO '22: Genetic and Evolutionary Computation Conference, Companion Volume, Boston, Massachusetts, USA, July 9 - 13, 2022. ACM 2022, ISBN 978-1-4503-9268-6 [contents] - [i15]Gregory A. Daly, Jonathan E. Fieldsend, Gavin R. Tabor:
Variational Autoencoders Without the Variation. CoRR abs/2203.00645 (2022) - [i14]Alma A. M. Rahat
Efficient Approximation of Expected Hypervolume Improvement using Gauss-Hermite Quadrature. CoRR abs/2206.07834 (2022) - [i13]Tianle Zhang, Wenjie Ruan, Jonathan E. Fieldsend:
PRoA: A Probabilistic Robustness Assessment against Functional Perturbations. CoRR abs/2207.02036 (2022) - [i12]Xiangyu Yin, Wenjie Ruan, Jonathan E. Fieldsend:
DIMBA: Discretely Masked Black-Box Attack in Single Object Tracking. CoRR abs/2207.08044 (2022) - 2021
- [j21]P. J. Watson, Jonathan E. Fieldsend, V. H. Stiles:
A scoping review using social network analysis techniques to summarise the prevalance of methods used to acquire data for athlete survelliance in sport. Int. J. Comput. Sci. Sport 20(2): 175-197 (2021) - [j20]Hao Wang, Chaoli Sun, Guochen Zhang, Jonathan E. Fieldsend, Yaochu Jin
Non-dominated sorting on performance indicators for evolutionary many-objective optimization. Inf. Sci. 551: 23-38 (2021) - [j19]Shufen Qin, Chaoli Sun, Yaochu Jin
Large-Scale Evolutionary Multiobjective Optimization Assisted by Directed Sampling. IEEE Trans. Evol. Comput. 25(4): 724-738 (2021) - [j18]George De Ath
Greed is Good: Exploration and Exploitation Trade-offs in Bayesian Optimisation. ACM Trans. Evol. Learn. Optim. 1(1): 1:1-1:22 (2021) - [c56]Finley J. Gibson, Richard M. Everson, Jonathan E. Fieldsend:
Multi-Objective Bayesian Optimisation Using an Exploitative Attainment Front Acquisition Function. CEC 2021: 1503-1510 - [c55]Carina Ivascu, Richard M. Everson
Optimising Diversity in Classifier Ensembles of Classification Trees. EvoApplications 2021: 634-648 - [c54]James Sakal, Jonathan E. Fieldsend, Edward C. Keedwell:
Learning assignment order in an ant colony optimiser for the university course timetabling problem. GECCO Companion 2021: 77-78 - [c53]Melike D. Karatas, Ozgur E. Akman, Jonathan E. Fieldsend:
Towards population-based fitness landscape analysis using local optima networks. GECCO Companion 2021: 1674-1682 - [c52]George De Ath
How Bayesian should Bayesian optimisation be? GECCO Companion 2021: 1860-1869 - [c51]George De Ath
Asynchronous ε-Greedy Bayesian Optimisation. UAI 2021: 578-588 - [p8]Mike Preuss, Michael Epitropakis, Xiaodong Li
Multimodal Optimization: Formulation, Heuristics, and a Decade of Advances. Metaheuristics for Finding Multiple Solutions 2021: 1-26 - [p7]Jonathan E. Fieldsend:
Representation, Resolution, and Visualization in Multimodal Optimization. Metaheuristics for Finding Multiple Solutions 2021: 27-55 - [p6]Khulood AlYahya, Kevin A. J. Doherty, Ozgur E. Akman, Jonathan E. Fieldsend:
Reduced Models of Gene Regulatory Networks: Visualising Multi-modal Landscapes. Metaheuristics for Finding Multiple Solutions 2021: 229-258 - [e1]Mike Preuss, Michael G. Epitropakis, Xiaodong Li, Jonathan E. Fieldsend:
Metaheuristics for Finding Multiple Solutions. Natural Computing Series, Springer 2021, ISBN 978-3-030-79552-8 [contents] - [i11]George De Ath, Richard M. Everson, Jonathan E. Fieldsend:
How Bayesian Should Bayesian Optimisation Be? CoRR abs/2105.00894 (2021) - 2020
- [c50]Jonathan E. Fieldsend:
Data structures for non-dominated sets: implementations and empirical assessment of two decades of advances. GECCO 2020: 489-497 - [c49]George De Ath
ϵ-shotgun: ϵ-greedy batch bayesian optimisation. GECCO 2020: 787-795 - [c48]George De Ath
What do you mean?: the role of the mean function in bayesian optimisation. GECCO Companion 2020: 1623-1631 - [i10]George De Ath, Richard M. Everson, Jonathan E. Fieldsend, Alma As-Aad Mohammad Rahat:
ε-shotgun: ε-greedy Batch Bayesian Optimisation. CoRR abs/2002.01873 (2020) - [i9]George De Ath, Jonathan E. Fieldsend, Richard M. Everson:
What do you Mean? The Role of the Mean Function in Bayesian Optimisation. CoRR abs/2004.08349 (2020) - [i8]George De Ath, Richard M. Everson, Jonathan E. Fieldsend:
Asynchronous ε-Greedy Bayesian Optimisation. CoRR abs/2010.07615 (2020)
2010 – 2019
- 2019
- [c47]Jonathan E. Fieldsend:
Efficient real-time hypervolume estimation with monotonically reducing error. GECCO 2019: 532-540 - [c46]Jonathan E. Fieldsend, Tinkle Chugh
A feature rich distance-based many-objective visualisable test problem generator. GECCO 2019: 541-549 - [c45]Khulood AlYahya, Ozgur E. Akman, Jonathan E. Fieldsend:
Landscape analysis under measurement error. GECCO (Companion) 2019: 1415-1418 - [c44]Jonathan E. Fieldsend, Khulood AlYahya:
Visualising the landscape of multi-objective problems using local optima networks. GECCO (Companion) 2019: 1421-1429 - [c43]Amjad A. Alsuwaylimi, Jonathan E. Fieldsend:
A New Initialisation Method for Examination Timetabling Heuristics. SSCI 2019: 1636-1643 - [c42]Abdulaziz T. Almutairi, Jonathan E. Fieldsend:
Automated and Surrogate Multi-Resolution Approaches in Genetic Algorithms. SSCI 2019: 2066-2073 - [i7]Nicholas D. Sanders, Richard M. Everson, Jonathan E. Fieldsend, Alma As-Aad Mohammad Rahat:
A Bayesian Approach for the Robust Optimisation of Expensive-To-Evaluate Functions. CoRR abs/1904.11416 (2019) - [i6]George De Ath, Richard M. Everson, Alma As-Aad Mohammad Rahat, Jonathan E. Fieldsend:
Greed is Good: Exploration and Exploitation Trade-offs in Bayesian Optimisation. CoRR abs/1911.12809 (2019) - 2018
- [c41]Kevin Anthony James Doherty, Khulood AlYahya, Jonathan E. Fieldsend, Ozgur E. Akman:
Voronoi-based archive sampling for robust optimisation. GECCO (Companion) 2018: 249-250 - [c40]Jonathan E. Fieldsend:
Computationally efficient local optima network construction. GECCO (Companion) 2018: 1481-1488 - [c39]Khulood AlYahya, Kevin Anthony James Doherty, Ozgur E. Akman, Jonathan E. Fieldsend:
Robust multi-modal optimisation. GECCO (Companion) 2018: 1783-1790 - [c38]Steven J. Daniels, Alma As-Aad Mohammad Rahat
A Suite of Computationally Expensive Shape Optimisation Problems Using Computational Fluid Dynamics. PPSN (2) 2018: 296-307 - 2017
- [j17]Yang Liu
A Framework of Fog Computing: Architecture, Challenges, and Optimization. IEEE Access 5: 25445-25454 (2017) - [c37]Khulood AlYahya, Kevin Anthony James Doherty, Jonathan E. Fieldsend, Ozgur E. Akman:
On the exploitation of search history and accumulative sampling in robust optimisation. GECCO (Companion) 2017: 185-186 - [c36]Samineh Bagheri, Wolfgang Konen
Constraint handling in efficient global optimization. GECCO 2017: 673-680 - [c35]Alma As-Aad Mohammad Rahat
Alternative infill strategies for expensive multi-objective optimisation. GECCO 2017: 873-880 - [c34]Jonathan E. Fieldsend
University staff teaching allocation: formulating and optimising a many-objective problem. GECCO 2017: 1097-1104 - [c33]Kevin Anthony James Doherty, Khulood AlYahya, Ozgur E. Akman, Jonathan E. Fieldsend
Optimisation and landscape analysis of computational biology models: a case study. GECCO (Companion) 2017: 1644-1651 - 2016
- [j16]Alma As-Aad Mohammad Rahat
Evolutionary multi-path routing for network lifetime and robustness in wireless sensor networks. Ad Hoc Networks 52: 130-145 (2016) - [c32]Alma As-Aad Rahat
Surrogate-Assisted Evolutionary Optimisation (SAEOpt'16) Chairs' Welcome & Organization. GECCO (Companion) 2016: 1265-1266 - [c31]Jonathan E. Fieldsend
Enabling Dominance Resistance in Visualisable Distance-Based Many-Objective Problems. GECCO (Companion) 2016: 1429-1436 - [c30]David J. Walker
Visualisation Methods in Genetic and Evolutionary Computation (VizGEC 2016) Chairs' Welcome & Organization. GECCO (Companion) 2016: 1445-1446 - 2015
- [j15]Alma As-Aad Mohammad Rahat
Hybrid Evolutionary Approaches to Maximum Lifetime Routing and Energy Efficiency in Sensor Mesh Networks. Evol. Comput. 23(3): 481-507 (2015) - [j14]Jonathan E. Fieldsend
Using an adaptive collection of local evolutionary algorithms for multi-modal problems. Soft Comput. 19(6): 1445-1460 (2015) - [j13]Jonathan E. Fieldsend
The Rolling Tide Evolutionary Algorithm: A Multiobjective Optimizer for Noisy Optimization Problems. IEEE Trans. Evol. Comput. 19(1): 103-117 (2015) - [c29]Jonathan E. Fieldsend
Elite Accumulative Sampling Strategies for Noisy Multi-objective Optimisation. EMO (2) 2015: 172-186 - [c28]Jonathan E. Fieldsend
Strength Through Diversity: Disaggregation and Multi-Objectivisation Approaches for Genetic Programming. GECCO 2015: 1031-1038 - 2014
- [j12]Richard M. Everson
Life on the Edge: Characterising the Edges of Mutually Non-dominating Sets. Evol. Comput. 22(3): 479-501 (2014) - [c27]Jonathan E. Fieldsend
Running Up Those Hills: Multi-modal search with the niching migratory multi-swarm optimiser. IEEE Congress on Evolutionary Computation 2014: 2593-2600 - [c26]Jonathan E. Fieldsend
Efficiently identifying pareto solutions when objective values change. GECCO 2014: 605-612 - [c25]Alma As-Aad Mohammad Rahat
Multi-objective routing optimisation for battery-powered wireless sensor mesh networks. GECCO 2014: 1175-1182 - 2013
- [j11]David J. Walker
Visualizing Mutually Nondominating Solution Sets in Many-Objective Optimization. IEEE Trans. Evol. Comput. 17(2): 165-184 (2013) - [c24]Jonathan E. Fieldsend
Visualising High-Dimensional Pareto Relationships in Two-Dimensional Scatterplots. EMO 2013: 558-572 - [c23]Matthaus Martin Woolard, Jonathan Edward Fieldsend
On the effect of selection and archiving operators in many-objective particle swarm optimisation. GECCO 2013: 129-136 - [c22]Richard M. Everson
Edges of mutually non-dominating sets. GECCO 2013: 607-614 - [c21]Jonathan E. Fieldsend
Multi-modal optimisation using a localised surrogates assisted evolutionary algorithm. UKCI 2013: 88-95 - 2012
- [c20]David J. Walker
Visualising many-objective populations. GECCO (Companion) 2012: 451-458 - 2011
- [c19]David J. Walker
Rank-based dimension reduction for many-criteria populations. GECCO (Companion) 2011: 107-108 - 2010
- [c18]William J. Reckhouse, Jonathan E. Fieldsend
Variable interactions and exploring parameter space in an expensive optimisation problem: Optimising Short Term Conflict Alert. IEEE Congress on Evolutionary Computation 2010: 1-8 - [c17]David J. Walker
Visualisation and ordering of many-objective populations. IEEE Congress on Evolutionary Computation 2010: 1-8 - [c16]Richard Fredlund, Richard M. Everson
A Bayesian framework for active learning. IJCNN 2010: 1-8 - [i5]Vitaly Schetinin, Jonathan E. Fieldsend, Derek Partridge, Wojtek J. Krzanowski, Richard M. Everson, Trevor C. Bailey, Adolfo Hernández:
A Bayesian Methodology for Estimating Uncertainty of Decisions in Safety-Critical Systems. CoRR abs/1012.0322 (2010)
2000 – 2009
- 2008
- [j10]Kevin I. Smith, Richard M. Everson
Dominance-Based Multiobjective Simulated Annealing. IEEE Trans. Evol. Comput. 12(3): 323-342 (2008) - [c15]Jonathan E. Fieldsend
On the efficient use of uncertainty when performing expensive ROC optimisation. IEEE Congress on Evolutionary Computation 2008: 3984-3991 - [p5]Jonathan E. Fieldsend, Richard M. Everson:
Multiobjective Supervised Learning. Multiobjective Problem Solving from Nature 2008: 155-176 - 2007
- [j9]Trevor C. Bailey, Richard M. Everson
Representing classifier confidence in the safety critical domain: an illustration from mortality prediction in trauma cases. Neural Comput. Appl. 16(1): 1-10 (2007) - [j8]Vitaly Schetinin, Jonathan E. Fieldsend
Confident Interpretation of Bayesian Decision Tree Ensembles for Clinical Applications. IEEE Trans. Inf. Technol. Biomed. 11(3): 312-319 (2007) - [p4]Vitaly Schetinin, Jonathan E. Fieldsend
Estimating Classification Uncertainty of Bayesian Decision TreeTechnique on Financial Data. Perception-based Data Mining and Decision Making in Economics and Finance 2007: 155-179 - 2006
- [j7]Wojtek J. Krzanowski, Trevor C. Bailey, Derek Partridge, Jonathan E. Fieldsend
Confidence in Classification: A Bayesian Approach. J. Classif. 23(2): 199-220 (2006) - [j6]Vitaly Schetinin, Jonathan E. Fieldsend
Comparison of the Bayesian and Randomised Decision Tree Ensembles within an Uncertainty Envelope Technique. J. Math. Model. Algorithms 5(4): 397-416 (2006) - [j5]Jovisa D. Zunic, Lazar Kopanja
Notes on shape orientation where the standard method does not work. Pattern Recognit. 39(5): 856-865 (2006) - [j4]Richard M. Everson
Multi-class ROC analysis from a multi-objective optimisation perspective. Pattern Recognit. Lett. 27(8): 918-927 (2006) - [j3]Richard M. Everson
Multiobjective Optimization of Safety Related Systems: An Application to Short-Term Conflict Alert. IEEE Trans. Evol. Comput. 10(2): 187-198 (2006) - [c14]Derek Partridge, Vitaly Schetinin, Dayou Li, Timothy J. Coats, Jonathan E. Fieldsend
Interpretability of Bayesian Decision Trees Induced from Trauma Data. ICAISC 2006: 972-981 - [c13]Richard M. Everson, Jonathan E. Fieldsend, Trevor C. Bailey, Wojtek J. Krzanowski, Derek Partridge, Vitaly Schetinin, Adolfo Hernández:
Optimising Data-Driven Safety Related Systems. SSS 2006: 217-230 - [c12]Derek Partridge, Trevor C. Bailey, Richard M. Everson, Jonathan E. Fieldsend, Adolfo Hernández, Wojtek J. Krzanowski, Vitaly Schetinin:
Classification with Confidence for Critical Systems. SSS 2006: 231-239 - [p3]Vitaly Schetinin, Jonathan E. Fieldsend, Derek Partridge, Wojtek J. Krzanowski, Richard M. Everson, Trevor C. Bailey, Adolfo Hernández:
A Bayesian Methodology for Estimating Uncertainty of Decisions in Safety-Critical Systems. Integrated Intelligent Systems for Engineering Design 2006: 82-96 - [p2]Jonathan E. Fieldsend:
Regression Error Characteristic Optimisation of Non-Linear Models. Multi-Objective Machine Learning 2006: 103-123 - [p1]Richard M. Everson, Jonathan E. Fieldsend:
Multi-Objective Optimisation for Receiver Operating Characteristic Analysis. Multi-Objective Machine Learning 2006: 533-556 - 2005
- [j2]Jonathan E. Fieldsend
Pareto evolutionary neural networks. IEEE Trans. Neural Networks 16(2): 338-354 (2005) - [c11]Jonathan E. Fieldsend, Richard M. Everson:
Multi-objective optimisation in the presence of uncertainty. Congress on Evolutionary Computation 2005: 243-250 - [c10]Julio E. Alvarez-Benitez, Richard M. Everson, Jonathan E. Fieldsend:
A MOPSO Algorithm Based Exclusively on Pareto Dominance Concepts. EMO 2005: 459-473 - [i4]Vitaly Schetinin, Jonathan E. Fieldsend, Derek Partridge, Wojtek J. Krzanowski, Richard M. Everson, Trevor C. Bailey, Adolfo Hernández:
The Bayesian Decision Tree Technique with a Sweeping Strategy. CoRR abs/cs/0504042 (2005) - [i3]Vitaly Schetinin, Derek Partridge, Wojtek J. Krzanowski, Richard M. Everson, Jonathan E. Fieldsend, Trevor C. Bailey, Adolfo Hernández:
Experimental Comparison of Classification Uncertainty for Randomised and Bayesian Decision Tree Ensembles. CoRR abs/cs/0504043 (2005) - [i2]Vitaly Schetinin, Jonathan E. Fieldsend, Derek Partridge, Wojtek J. Krzanowski, Richard M. Everson, Trevor C. Bailey, Adolfo Hernández:
Estimating Classification Uncertainty of Bayesian Decision Tree Technique on Financial Data. CoRR abs/cs/0504065 (2005) - [i1]Vitaly Schetinin, Jonathan E. Fieldsend, Derek Partridge, Wojtek J. Krzanowski, Richard M. Everson, Trevor C. Bailey, Adolfo Hernández:
Comparison of the Bayesian and Randomised Decision Tree Ensembles within an Uncertainty Envelope Technique. CoRR abs/cs/0504066 (2005) - 2004
- [c9]Kevin I. Smith, Richard M. Everson, Jonathan E. Fieldsend:
Dominance measures for multi-objective simulated annealing. IEEE Congress on Evolutionary Computation 2004: 23-30 - [c8]Richard M. Everson, Jonathan E. Fieldsend:
A Variable Metric Probabilistic k-Nearest-Neighbours Classifier. IDEAL 2004: 654-659 - [c7]Vitaly Schetinin, Derek Partridge, Wojtek J. Krzanowski, Richard M. Everson, Jonathan E. Fieldsend, Trevor C. Bailey, Adolfo Hernández
Experimental Comparison of Classification Uncertainty for Randomised and Bayesian Decision Tree Ensembles. IDEAL 2004: 726-732 - [c6]Jonathan E. Fieldsend, John Matatko, Ming Peng:
Cardinality Constrained Portfolio Optimisation. IDEAL 2004: 788-793 - [c5]Jonathan E. Fieldsend, Richard M. Everson:
ROC Optimisation of Safety Related Systems. ROCAI 2004: 37-44 - [c4]Michelle Jayne Fisher, Jonathan E. Fieldsend, Richard M. Everson:
Precision and Recall Optimisation for Information Access Tasks. ROCAI 2004: 45-54 - 2003
- [b1]Jonathan E. Fieldsend:
Novel algorithms for multi-objective search and their application in multi-objective evolutionary neural network training. University of Exeter, Devon, UK, 2003 - [j1]Jonathan E. Fieldsend
Using unconstrained elite archives for multiobjective optimization. IEEE Trans. Evol. Comput. 7(3): 305-323 (2003) - 2001
- [c3]Sameer Singh, Jonathan E. Fieldsend:
Pattern Matching and Neural Networks Based Hybrid Forecasting System. ICAPR 2001: 72-82 - 2000
- [c2]Sameer Singh, Jonathan E. Fieldsend:
Financial time series forecasts using fuzzy and long memory pattern recognition systems. CIFEr 2000: 166-169 - [c1]Keir Bovis, Sameer Singh, Jonathan E. Fieldsend, Chris Pinder:
Identification of Masses in Digital Mammograms with MLP and RBF Nets. IJCNN (1) 2000: 342-347
Coauthor Index
[j23] [c59] [j18] [c56] [c55] [c52] [c51] [i11] [c49] [c48] [i10] [i9] [i8] [i7] [i6] [c38] [c35] [j16] [c32] [c30] [j15] [j13] [j12] [c26] [c25] [j11] [c24] [c22] [c20] [c19] [c18] [c17] [c16] [i5] [j10] [c15] [p5] [j9] [j8] [p4] [j7] [j6] [j4] [j3] [c14] [c13] [c12] [p3] [p1] [c11] [c10] [i4] [i3] [i2] [i1] [c9] [c8] [c7] [c5] [c4] [j1]
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