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Michael A. Lones
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2020 – today
- 2024
- [i15]Kahraman Kostas, Mike Just, Michael A. Lones:
IoTGeM: Generalizable Models for Behaviour-Based IoT Attack Detection. CoRR abs/2401.01343 (2024) - [i14]Ali Muzaffar, Hani Ragab Hassen, Hind Zantout, Michael A. Lones:
ActDroid: An active learning framework for Android malware detection. CoRR abs/2401.16982 (2024) - [i13]Kahraman Kostas, Mike Just, Michael A. Lones:
Individual Packet Features are a Risk to Model Generalisation in ML-Based Intrusion Detection. CoRR abs/2406.07578 (2024) - 2023
- [i12]Ali Muzaffar, Hani Ragab Hassen, Hind Zantout, Michael A. Lones:
A Comprehensive Investigation of Feature and Model Importance in Android Malware Detection. CoRR abs/2301.12778 (2023) - [i11]Kahraman Kostas, Mike Just, Michael A. Lones:
Externally validating the IoTDevID device identification methodology using the CIC IoT 2022 Dataset. CoRR abs/2307.08679 (2023) - [i10]Ali Muzaffar, Hani Ragab Hassen, Hind Zantout, Michael A. Lones:
DroidDissector: A Static and Dynamic Analysis Tool for Android Malware Detection. CoRR abs/2308.04170 (2023) - [i9]Sayash Kapoor, Emily Cantrell, Kenny Peng, Thanh Hien Pham, Christopher A. Bail, Odd Erik Gundersen, Jake M. Hofman, Jessica Hullman, Michael A. Lones, Momin M. Malik, Priyanka Nanayakkara, Russell A. Poldrack, Inioluwa Deborah Raji, Michael Roberts, Matthew J. Salganik, Marta Serra-Garcia, Brandon M. Stewart, Gilles Vandewiele, Arvind Narayanan:
REFORMS: Reporting Standards for Machine Learning Based Science. CoRR abs/2308.07832 (2023) - 2022
- [j24]Ali Muzaffar, Hani Ragab Hassen, Michael A. Lones, Hind Zantout:
An in-depth review of machine learning based Android malware detection. Comput. Secur. 121: 102833 (2022) - [j23]Kahraman Kostas, Mike Just, Michael A. Lones:
IoTDevID: A Behavior-Based Device Identification Method for the IoT. IEEE Internet Things J. 9(23): 23741-23749 (2022) - [j22]Mohamad Alissa, Michael A. Lones, Jeremy Cosgrove, Jane E. Alty, Stuart Jamieson, Stephen L. Smith, Marta Vallejo:
Parkinson's disease diagnosis using convolutional neural networks and figure-copying tasks. Neural Comput. Appl. 34(2): 1433-1453 (2022) - [c39]Daniel Kienitz, Ekaterina Komendantskaya, Michael A. Lones:
The Effect of Manifold Entanglement and Intrinsic Dimensionality on Learning. AAAI 2022: 7160-7167 - [c38]Daniel Kienitz, Ekaterina Komendantskaya, Michael A. Lones:
Comparing Complexities of Decision Boundaries for Robust Training: A Universal Approach. ACCV (6) 2022: 627-645 - [c37]Heba El-Shimy, Hind Zantout, Michael A. Lones, Neamat El Gayar:
A Review of Capsule Networks in Medical Image Analysis. ANNPR 2022: 65-80 - [c36]Fraser Garrow, Michael A. Lones, Robert J. Stewart:
Why functional program synthesis matters (in the realm of genetic programming). GECCO Companion 2022: 1844-1853 - 2021
- [j21]Caetano Mazzoni Ranieri, Jhielson M. Pimentel, Marcelo R. Romano, Leonardo Abdala Elias, Roseli A. F. Romero, Michael A. Lones, Mariana F. P. Araújo, Patrícia A. Vargas, Renan Cipriano Moioli:
A Data-Driven Biophysical Computational Model of Parkinson's Disease Based on Marmoset Monkeys. IEEE Access 9: 122548-122567 (2021) - [j20]Michael A. Lones:
Evolving continuous optimisers from scratch. Genet. Program. Evolvable Mach. 22(4): 395-428 (2021) - [j19]Nadia S. Taou, Michael A. Lones:
Optimising Boolean Synthetic Regulatory Networks to Control Cell States. IEEE ACM Trans. Comput. Biol. Bioinform. 18(6): 2649-2658 (2021) - [c35]Arjun Shenoy A. V, Michael A. Lones, Stephen L. Smith, Marta Vallejo:
Evaluation of Recurrent Neural Network Models for Parkinson's Disease Classification Using Drawing Data. EMBC 2021: 1702-1706 - [c34]Filip Wieslaw Bartoszewski, Mike Just, Michael A. Lones, Oleksii Mandrychenko:
Anomaly Detection for Insider Threats: An Objective Comparison of Machine Learning Models and Ensembles. SEC 2021: 367-381 - [i8]Kahraman Kostas, Mike Just, Michael A. Lones:
IoTDevID: A Behaviour-Based Fingerprinting Method for Device Identification in the IoT. CoRR abs/2102.08866 (2021) - [i7]Michael A. Lones:
Evolving Continuous Optimisers from Scratch. CoRR abs/2103.11746 (2021) - [i6]Caetano Mazzoni Ranieri, Jhielson M. Pimentel, Marcelo R. Romano, Leonardo Abdala Elias, Roseli A. F. Romero, Michael A. Lones, Mariana F. P. Araújo, Patrícia A. Vargas, Renan Cipriano Moioli:
A Data-Driven Biophysical Computational Model of Parkinson's Disease based on Marmoset Monkeys. CoRR abs/2107.12536 (2021) - [i5]Michael A. Lones:
How to avoid machine learning pitfalls: a guide for academic researchers. CoRR abs/2108.02497 (2021) - 2020
- [j18]Michael A. Lones:
Mitigating Metaphors: A Comprehensible Guide to Recent Nature-Inspired Algorithms. SN Comput. Sci. 1(1): 49:1-49:12 (2020) - [c33]Amani M. Benhalem, Michael A. Lones:
Neural-Guided Particle Swarm optimization. CEC 2020: 1-7 - [c32]Michael A. Lones:
Optimising Optimisers with Push GP. EuroGP 2020: 101-117 - [c31]Kirsty Duncan, Ekaterina Komendantskaya, Robert J. Stewart, Michael A. Lones:
Relative Robustness of Quantized Neural Networks Against Adversarial Attacks. IJCNN 2020: 1-8
2010 – 2019
- 2019
- [j17]Alexander P. Turner, Andrew M. Tyrrell, Martin Trefzer, Michael A. Lones:
Evolutionary acquisition of complex traits in artificial epigenetic networks. Biosyst. 176: 17-26 (2019) - [c30]Michael A. Lones:
Instruction-level design of local optimisers using push GP. GECCO (Companion) 2019: 1487-1494 - [i4]Michael Adam Lones:
Mitigating Metaphors: A Comprehensible Guide to Recent Nature-Inspired Algorithms. CoRR abs/1902.08001 (2019) - [i3]Michael A. Lones:
Instruction-Level Design of Local Optimisers using Push GP. CoRR abs/1905.10245 (2019) - [i2]Michael A. Lones:
Optimising Optimisers with Push GP. CoRR abs/1910.00945 (2019) - 2018
- [j16]Stuart E. Lacy, Stephen L. Smith, Michael A. Lones:
Using echo state networks for classification: A case study in Parkinson's disease diagnosis. Artif. Intell. Medicine 86: 53-59 (2018) - [j15]Nadia S. Taou, David W. Corne, Michael A. Lones:
Investigating the use of Boolean networks for the control of gene regulatory networks. J. Comput. Sci. 26: 147-156 (2018) - [c29]Nadia S. Taou, Michael A. Lones:
Towards in Vivo Genetic Programming: Evolving Boolean Networks to Determine Cell States. EuroGP 2018: 151-165 - [r1]David Corne, Michael A. Lones:
Evolutionary Algorithms. Handbook of Heuristics 2018: 409-430 - [i1]David W. Corne, Michael A. Lones:
Evolutionary Algorithms. CoRR abs/1805.11014 (2018) - 2017
- [j14]Michael A. Lones, Jane E. Alty, Jeremy Cosgrove, Philippa Duggan-Carter, Stuart Jamieson, Rebecca F. Naylor, Andrew James Turner, Stephen L. Smith:
A New Evolutionary Algorithm-Based Home Monitoring Device for Parkinson's Dyskinesia. J. Medical Syst. 41(11): 176:1-176:8 (2017) - [j13]Alexander P. Turner, Leo S. D. Caves, Susan Stepney, Andy M. Tyrrell, Michael A. Lones:
Artificial Epigenetic Networks: Automatic Decomposition of Dynamical Control Tasks Using Topological Self-Modification. IEEE Trans. Neural Networks Learn. Syst. 28(1): 218-230 (2017) - [c28]Michael A. Lones, Jane E. Alty, Jeremy Cosgrove, Stuart Jamieson, Stephen L. Smith:
Going through directional changes: evolving human movement classifiers using an event based encoding. GECCO (Companion) 2017: 1365-1371 - 2016
- [j12]Andy M. Tyrrell, Michael A. Lones, Stephen L. Smith, Gary B. Fogel:
2015 Information Processing in Cells and Tissues (IPCAT 2015). Biosyst. 146: 1-2 (2016) - [j11]Alexander P. Turner, Michael A. Lones, Martin A. Trefzer, Stephen L. Smith, Stuart Jamieson, Jane E. Alty, Jeremy Cosgrove, Andy M. Tyrrell:
Using epigenetic networks for the analysis of movement associated with levodopa therapy for Parkinson's disease. Biosyst. 146: 35-42 (2016) - [c27]Nadia S. Taou, David W. Corne, Michael A. Lones:
Evolving Boolean networks for biological control: State space targeting in scale free Boolean networks. CIBCB 2016: 1-6 - [c26]Nadia S. Taou, David W. Corne, Michael A. Lones:
Towards Intelligent Biological Control: Controlling Boolean Networks with Boolean Networks. EvoApplications (1) 2016: 351-362 - [c25]Marta Vallejo, Jeremy Cosgrove, Jane E. Alty, Stephen L. Smith, David W. Corne, Michael A. Lones:
Using Multiobjective Evolutionary Algorithms to Understand Parkinson's Disease. GECCO (Companion) 2016: 13-14 - [c24]Marta Vallejo, Jeremy Cosgrove, Jane E. Alty, Stuart Jamieson, Stephen L. Smith, David W. Corne, Michael A. Lones:
A Multi-Objective Approach to Predicting Motor and Cognitive Deficit in Parkinson's Disease Patients. GECCO (Companion) 2016: 1369-1376 - [c23]Marta Vallejo, Stuart Jamieson, Jeremy Cosgrove, Stephen L. Smith, Michael A. Lones, Jane E. Alty, David W. Corne:
Exploring diagnostic models of Parkinson's disease with multi-objective regression. SSCI 2016: 1-8 - 2015
- [c22]Stuart E. Lacy, Michael A. Lones, Stephen L. Smith:
Forming classifier ensembles with multimodal Evolutionary Algorithms. CEC 2015: 723-729 - [c21]Stuart E. Lacy, Michael A. Lones, Stephen L. Smith:
A comparison of evolved linear and non-linear ensemble vote aggregators. CEC 2015: 758-763 - [c20]Michael A. Lones, Stuart E. Lacy, Stephen L. Smith:
Evolving Ensembles: What Can We Learn from Biological Mutualisms? IPCAT 2015: 52-60 - [c19]Luis A. Fuente, Michael A. Lones, Nigel T. Crook, Tjeerd Olde Scheper:
Harmonic Versus Chaos Controlled Oscillators in Hexapedal Locomotion. IPCAT 2015: 114-127 - [c18]Alexander P. Turner, Martin A. Trefzer, Michael A. Lones, Andy M. Tyrrell:
Evolving Efficient Solutions to Complex Problems Using the Artificial Epigenetic Network. IPCAT 2015: 153-165 - [p3]Michael A. Lones, Stephen L. Smith:
Medical Applications of Evolvable Hardware. Evolvable Hardware 2015: 253-271 - [e2]Michael A. Lones, Andy M. Tyrrell, Stephen L. Smith, Gary B. Fogel:
Information Processing in Cells and Tissues - 10th International Conference, IPCAT 2015, San Diego, CA, USA, September 14-16, 2015, Proceedings. Lecture Notes in Computer Science 9303, Springer 2015, ISBN 978-3-319-23107-5 [contents] - 2014
- [j10]Michael A. Lones, Luis A. Fuente, Alexander P. Turner, Leo S. D. Caves, Susan Stepney, Stephen L. Smith, Andy M. Tyrrell:
Artificial Biochemical Networks: Evolving Dynamical Systems to Control Dynamical Systems. IEEE Trans. Evol. Comput. 18(2): 145-166 (2014) - [j9]Michael A. Lones, Stephen L. Smith, Jane E. Alty, Stuart E. Lacy, Katherine L. Possin, D. R. Stuart Jamieson, Andy M. Tyrrell:
Evolving Classifiers to Recognize the Movement Characteristics of Parkinson's Disease Patients. IEEE Trans. Evol. Comput. 18(4): 559-576 (2014) - [c17]Michael A. Lones, Jane E. Alty, Philippa Duggan-Carter, Andrew James Turner, D. R. Stuart Jamieson, Stephen L. Smith:
Classification and characterisation of movement patterns during levodopa therapy for parkinson's disease. GECCO (Companion) 2014: 1321-1328 - [c16]Michael A. Lones:
Metaheuristics in nature-inspired algorithms. GECCO (Companion) 2014: 1419-1422 - 2013
- [j8]Alexander P. Turner, Michael A. Lones, Luis A. Fuente, Susan Stepney, Leo S. D. Caves, Andy M. Tyrrell:
The incorporation of epigenetics in artificial gene regulatory networks. Biosyst. 112(2): 56-62 (2013) - [j7]Michael A. Lones, Stephen L. Smith, Andy M. Tyrrell, Jane E. Alty, D. R. Stuart Jamieson:
Characterising neurological time series data using biologically motivated networks of coupled discrete maps. Biosyst. 112(2): 94-101 (2013) - [j6]Luis A. Fuente, Michael A. Lones, Alexander P. Turner, Susan Stepney, Leo S. D. Caves, Andy M. Tyrrell:
Computational models of signalling networks for non-linear control. Biosyst. 112(2): 122-130 (2013) - [j5]Michael A. Lones, Andy M. Tyrrell, Susan Stepney, Leo S. D. Caves:
Special issue on the frontiers of natural computing. Nat. Comput. 12(4): 441-442 (2013) - [j4]Michael A. Lones, Alexander P. Turner, Luis A. Fuente, Susan Stepney, Leo S. D. Caves, Andy M. Tyrrell:
Biochemical connectionism. Nat. Comput. 12(4): 453-472 (2013) - [c15]Luis A. Fuente, Michael A. Lones, Alexander P. Turner, Leo S. D. Caves, Susan Stepney, Andy M. Tyrrell:
Adaptive robotic gait control using coupled artificial signalling networks, hopf oscillators and inverse kinematics. IEEE Congress on Evolutionary Computation 2013: 1435-1442 - [c14]Michael A. Lones, Jane E. Alty, Stuart E. Lacy, D. R. Stuart Jamieson, Katherine L. Possin, Norbert Schuff, Stephen L. Smith:
Evolving classifiers to inform clinical assessment of Parkinson's disease. CICARE 2013: 76-82 - [c13]Stuart E. Lacy, Michael A. Lones, Stephen L. Smith, Jane E. Alty, D. R. Stuart Jamieson, Katherine L. Possin, Norbert Schuff:
Characterisation of movement disorder in parkinson's disease using evolutionary algorithms. GECCO (Companion) 2013: 1479-1486 - [c12]Alexander P. Turner, Michael A. Lones, Luis A. Fuente, Susan Stepney, Leo S. D. Caves, Andy M. Tyrrell:
The artificial epigenetic network. ICES 2013: 66-72 - 2012
- [c11]Alexander P. Turner, Michael A. Lones, Luis A. Fuente, Susan Stepney, Leo S. D. Caves, Andy M. Tyrrell:
Using Artificial Epigenetic Regulatory Networks to Control Complex Tasks within Chaotic Systems. IPCAT 2012: 1-11 - [c10]Luis A. Fuente, Michael A. Lones, Alexander P. Turner, Susan Stepney, Leo S. D. Caves, Andy M. Tyrrell:
Evolved Artificial Signalling Networks for the Control of a Conservative Complex Dynamical System. IPCAT 2012: 38-49 - [c9]Michael A. Lones, Stephen L. Smith, Andy M. Tyrrell, Jane E. Alty, D. R. Stuart Jamieson:
Evolving Computational Dynamical Systems to Recognise Abnormal Human Motor Function. IPCAT 2012: 177-182 - [e1]Michael A. Lones, Stephen L. Smith, Sarah A. Teichmann, Felix Naef, James Alfred Walker, Martin Trefzer:
Information Processign in Cells and Tissues - 9th International Conference, IPCAT 2012, Cambridge, UK, March 31 - April 2, 2012. Proceedings. Lecture Notes in Computer Science 7223, Springer 2012, ISBN 978-3-642-28791-6 [contents] - 2011
- [j3]Michael A. Lones:
Sean Luke: essentials of metaheuristics. Genet. Program. Evolvable Mach. 12(3): 333-334 (2011) - [c8]Michael A. Lones, Andy M. Tyrrell, Susan Stepney, Leo S. D. Caves:
Controlling legged robots with coupled artificial biochemical networks. ECAL 2011: 465-472 - [p2]Michael A. Lones, Stephen L. Smith:
Objective Assessment of Visuo-spatial Ability using Implicit Context Representation Cartesian Genetic Programming. Genetic and Evolutionary Computation: Medical Applications 2011 - 2010
- [c7]Michael A. Lones, Stephen L. Smith, Andrew T. Harris, Alec S. High, Sheila E. Fisher, D. Alastair Smith, Jennifer Kirkham:
Discriminating normal and cancerous thyroid cell lines using implicit context representation Cartesian genetic programming. IEEE Congress on Evolutionary Computation 2010: 1-6 - [c6]Michael A. Lones, Andy M. Tyrrell, Susan Stepney, Leo S. D. Caves:
Controlling Complex Dynamics with Artificial Biochemical Networks. EuroGP 2010: 159-170
2000 – 2009
- 2009
- [c5]Stephen L. Smith, Michael A. Lones:
Implicit Context Representation Cartesian Genetic Programming for the assessment of visuo-spatial ability. IEEE Congress on Evolutionary Computation 2009: 1072-1078 - 2007
- [j2]Michael A. Lones, Andy M. Tyrrell:
Regulatory Motif Discovery Using a Population Clustering Evolutionary Algorithm. IEEE ACM Trans. Comput. Biol. Bioinform. 4(3): 403-414 (2007) - [c4]Michael A. Lones, Andy M. Tyrrell:
A co-evolutionary framework for regulatory motif discovery. IEEE Congress on Evolutionary Computation 2007: 3894-3901 - 2005
- [c3]Michael A. Lones, Andrew M. Tyrrell:
The evolutionary computation approach to motif discovery in biological sequences. GECCO Workshops 2005: 1-11 - 2004
- [p1]Michael A. Lones, Andy M. Tyrrell:
Enzyme Genetic Programming. Cellular Computing 2004: 19-42 - 2003
- [b1]Michael Adam Lones:
Enzyme genetic programming : modelling biological evolvability in genetic programming. University of York, UK, 2003 - 2002
- [j1]Michael A. Lones, Andrew M. Tyrrell:
Biomimetic Representation with Genetic Programming Enzyme. Genet. Program. Evolvable Mach. 3(2): 193-217 (2002) - [c2]Michael A. Lones, Andy M. Tyrrell:
Crossover and bloat in the functionality model of enzyme genetic programming. IEEE Congress on Evolutionary Computation 2002: 986-991 - 2001
- [c1]Michael A. Lones, Andy M. Tyrrell:
Enzyme genetic programming. CEC 2001: 1183-1190
Coauthor Index
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last updated on 2024-08-05 21:24 CEST by the dblp team
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