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Mardé Helbig
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- affiliation: Griffith University, School of Information and Communication Technology, Australia
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2020 – today
- 2024
- [c44]Mardé Helbig:
Dynamic Multi-objective Optimisation Problems with Changes of Varying Frequency and Severity. CEC 2024: 1-8 - 2023
- [j6]Adekunle Rotimi Adekoya, Mardé Helbig:
Decision-Maker's Preference-Driven Dynamic Multi-Objective Optimization. Algorithms 16(11): 504 (2023) - [c43]Anna Sergeevna Bosman, Andries P. Engelbrecht, Mardé Helbig:
Empirical Loss Landscape Analysis of Neural Network Activation Functions. GECCO Companion 2023: 2029-2037 - [e1]Jun Jo, Han-Lim Choi, Mardé Helbig, Hyondong Oh, Jemin Hwangbo, Chang-Hun Lee, Bela Stantic:
Robot Intelligence Technology and Applications 7 - Results from the 10th International Conference on Robot Intelligence Technology and Applications, RiTA 2022, Daejeon, South Korea, 7-9 December, 2022. Lecture Notes in Networks and Systems 642, Springer 2023, ISBN 978-3-031-26888-5 [contents] - [i3]Anna Sergeevna Bosman, Andries P. Engelbrecht, Mardé Helbig:
Empirical Loss Landscape Analysis of Neural Network Activation Functions. CoRR abs/2306.16090 (2023) - 2022
- [c42]Ojaswini Malhotra, Sharmistha Dey, Ernest Foo, Mardé Helbig:
Cybersecurity Maturity Model Capability in Aviation and Railway Industry. ACIS 2022: 23 - 2021
- [c41]Ojaswini Malhotra, Sharmistha Dey, Ernest Foo, Mardé Helbig:
Cyber Security Maturity Model Capability at The Airports. ACIS 2021: 55 - [c40]Mardé Helbig:
Dynamic multi-objective optimization: introduction, challenges, applications and future directions. GECCO Companion 2021: 818-838 - 2020
- [j5]Anna Sergeevna Bosman, Andries P. Engelbrecht, Mardé Helbig:
Visualising basins of attraction for the cross-entropy and the squared error neural network loss functions. Neurocomputing 400: 113-136 (2020) - [c39]Bernard van Tonder, Mardé Helbig:
Dynamic Multi-objective Optimisation Problems with Intertemporal Dependencies. GECCO Companion 2020: 179-180 - [c38]Anna Sergeevna Bosman, Andries P. Engelbrecht, Mardé Helbig:
Loss Surface Modality of Feed-Forward Neural Network Architectures. IJCNN 2020: 1-8 - [c37]Andries P. Engelbrecht, Mardé Helbig:
Empirical Analysis of A Partial Dominance Approach to Many-Objective Optimisation. ISMSI 2020: 71-75 - [c36]Mardé Helbig, Andries P. Engelbrecht:
Partial Dominance for Many-Objective Optimization. ISMSI 2020: 81-86 - [c35]Nyiko Cecil Musisinyani, Jacomine Grobler, Mardé Helbig:
Weather Downtime Prediction in a South African Port Environment. SGAI Conf. 2020: 241-255
2010 – 2019
- 2019
- [c34]Frederick Ditliac Atiah, Mardé Helbig:
Effects of Decision Models on Dynamic Multi-objective Optimization Algorithms for Financial Markets. CEC 2019: 762-770 - [c33]Mardé Helbig, Heiner Zille, Mahrokh Javadi, Sanaz Mostaghim:
Performance of dynamic algorithms on the dynamic distance minimization problem. GECCO (Companion) 2019: 205-206 - [i2]Anna Sergeevna Bosman, Andries P. Engelbrecht, Mardé Helbig:
Visualising Basins of Attraction for the Cross-Entropy and the Squared Error Neural Network Loss Functions. CoRR abs/1901.02302 (2019) - [i1]Anna Sergeevna Bosman, Andries P. Engelbrecht, Mardé Helbig:
Loss Surface Modality of Feed-Forward Neural Network Architectures. CoRR abs/1905.10268 (2019) - 2018
- [j4]Anna S. Bosman, Andries P. Engelbrecht, Mardé Helbig:
Fitness Landscape Analysis of Weight-Elimination Neural Networks. Neural Process. Lett. 48(1): 353-373 (2018) - [c32]Anna Sergeevna Bosman, Andries P. Engelbrecht, Mardé Helbig:
Progressive gradient walk for neural network fitness landscape analysis. GECCO (Companion) 2018: 1473-1480 - [c31]Mardé Helbig:
Visualising the search process for multi-objective optimisation. GECCO (Companion) 2018: 1560-1561 - [c30]Bayanda Chakuma, Mardé Helbig:
Visualizing the Optimization Process for Multi-objective Optimization Problems. ICAISC (1) 2018: 333-344 - [c29]Rohan Hemansu Chhipa, Mardé Helbig:
Comparison of Constraint Handling Approaches in Multi-objective Optimization. ICAISC (1) 2018: 345-362 - [c28]Armand Maree, Marius Riekert, Mardé Helbig:
Deriving Functions for Pareto Optimal Fronts Using Genetic Programming. ICAISC (1) 2018: 462-473 - [c27]Frederick Ditliac Atiah, Mardé Helbig:
Dynamic Particle Swarm Optimization for Financial Markets. SSCI 2018: 2337-2344 - 2017
- [c26]R. Adekoya Adekunle, Mardé Helbig:
A differential evolution algorithm for dynamic multi-objective optimization. SSCI 2017: 1-10 - [c25]Frikkie Snyman, Mardé Helbig:
Solving Constrained Multi-objective Optimization Problems with Evolutionary Algorithms. ICSI (2) 2017: 57-66 - [c24]Zühnja Riekert, Mardé Helbig:
Solving Inverse Kinematics with Vector Evaluated Particle Swarm Optimization. ICSI (1) 2017: 225-237 - 2016
- [c23]Mardé Helbig, Kalyanmoy Deb, Andries P. Engelbrecht:
Key challenges and future directions of dynamic multi-objective optimisation. CEC 2016: 1256-1261 - [c22]Anna Sergeevna Bosman, Andries P. Engelbrecht, Mardé Helbig:
Search space boundaries in neural network error landscape analysis. SSCI 2016: 1-8 - [c21]Mardé Helbig:
Padding the dimensions for knowledge transfer in the dynamic vector evaluated particle swarm optimisation algorithm. SSCI 2016: 1-8 - [c20]Dieter Doman, Mardé Helbig, Andries P. Engelbrecht:
Heterogeneous Vector-Evaluated Particle Swarm Optimisation in Static Environments. ICSI (1) 2016: 293-304 - 2015
- [c19]Mardé Helbig, Andries P. Engelbrecht:
Influence of the archive size on the performance of the dynamic vector evaluated particle swarm optimisation algorithm solving dynamic multi-objective optimisation problems. CEC 2015: 1926-1933 - [c18]Mardé Helbig, Andries P. Engelbrecht:
The Effect of Quantum and Charged Particles on the Performance of the Dynamic Vector-evaluated Particle Swarm Optimisation Algorithm. GECCO 2015: 25-32 - [c17]Mardé Helbig, Andries P. Engelbrecht:
Using Headless Chicken Crossover for Local Guide Selection When Solving Dynamic Multi-objective Optimization. NaBIC 2015: 381-392 - [c16]Mardé Helbig:
Updating the Global Best and Archive Solutions of the Dynamic Vector-Evaluated PSO Algorithm Using \epsilon ϵ -dominance. NaBIC 2015: 393-403 - [c15]Mardé Helbig, Andries P. Engelbrecht:
Dynamic Vector-Evaluated PSO with Guaranteed Convergence in the Sub-Swarms. SSCI 2015: 1286-1293 - 2014
- [j3]Mardé Helbig, Andries P. Engelbrecht:
Benchmarks for dynamic multi-objective optimisation algorithms. ACM Comput. Surv. 46(3): 37:1-37:39 (2014) - [j2]Mardé Helbig, Andries P. Engelbrecht:
Population-based metaheuristics for continuous boundary-constrained dynamic multi-objective optimisation problems. Swarm Evol. Comput. 14: 31-47 (2014) - [c14]Mardé Helbig, Andries P. Engelbrecht:
Heterogeneous dynamic vector evaluated particle swarm optimisation for dynamic multi-objective optimisation. IEEE Congress on Evolutionary Computation 2014: 3151-3159 - [c13]Mardé Helbig, Andries P. Engelbrecht:
Using heterogeneous knowledge sharing strategies with dynamic vector-evaluated particle swarm optimisation. SIS 2014: 259-266 - 2013
- [j1]Mardé Helbig, Andries P. Engelbrecht:
Performance measures for dynamic multi-objective optimisation algorithms. Inf. Sci. 250: 61-81 (2013) - [c12]Mardé Helbig, Andries P. Engelbrecht:
Analysing the performance of dynamic multi-objective optimisation algorithms. IEEE Congress on Evolutionary Computation 2013: 1531-1539 - [c11]Mardé Helbig, Andries P. Engelbrecht:
Issues with performance measures for dynamic multi-objective optimisation. CIDUE 2013: 17-24 - [c10]Mardé Helbig, Andries P. Engelbrecht:
Benchmarks for dynamic multi-objective optimisation. CIDUE 2013: 84-91 - [p2]Mardé Helbig, Andries P. Engelbrecht:
Dynamic Multi-Objective Optimization Using PSO. Metaheuristics for Dynamic Optimization 2013: 147-188 - 2012
- [c9]Mardé Helbig, Andries P. Engelbrecht:
Analyses of guide update approaches for vector evaluated particle swarm optimisation on dynamic multi-objective optimisation problems. IEEE Congress on Evolutionary Computation 2012: 1-8 - 2011
- [c8]Mardé Helbig, Andries P. Engelbrecht:
Archive management for dynamic multi-objective optimisation problems using vector evaluated particle swarm optimisation. IEEE Congress on Evolutionary Computation 2011: 2047-2054 - 2010
- [c7]Mardé Greeff, Quentin Williams, Ronéll Alberts, Harriet Pretorius:
Determining the user profile for an adaptable training platform. SAICSIT 2010: 365-369 - [p1]Mardé Greeff, Andries P. Engelbrecht:
Dynamic Multi-objective Optimisation Using PSO. Multi-Objective Swarm Intelligent System 2010: 105-123
2000 – 2009
- 2009
- [c6]Mardé Greeff, Paula Kotzé:
A lightweight methodology to improve web accessibility. SAICSIT 2009: 30-39 - 2008
- [c5]Mardé Greeff, Andries P. Engelbrecht:
Solving dynamic multi-objective problems with vector evaluated particle swarm optimisation. IEEE Congress on Evolutionary Computation 2008: 2917-2924 - [c4]Mardé Greeff, Louis Coetzee, Martin Pistorius:
Usability evaluation of the South African National Accessibility Portal interactive voice response system. SAICSIT 2008: 76-85 - 2005
- [c3]Mardé Greeff, Jörg Haber, Hans-Peter Seidel:
Nailing and Pinning: Adding Constraints to Inverse Kinematics . WSCG (Short Papers) 2005: 125-128 - 2001
- [c2]Mardé Greeff, Vali Lalioti:
Interactive Storytelling with Virtual Identities. EGVE/IPT 2001: 121-130 - [c1]Mardé Greeff, Vali Lalioti:
Interactive Cultural Experiences Using Virtual Identities. ICHIM (1) 2001: 455-465
Coauthor Index
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last updated on 2024-10-07 21:23 CEST by the dblp team
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