Computational Intelligence
- Computational Intelligence
- Computational Intelligence
Prof. Ofer Shir
Multi-objective mixed-integer quadratic models: A study on mathematical programming and evolutionary computation
Shir, O. M & Emmerich. M.
IEEE Trans. Evol. Comp. doi: 10.1109/TEVC.2024.3374519
2024
Avoiding Redundant Restarts in Multimodal Global Optimization
de Nobel, J., Vermetten, D., Kononova, A.V., Shir, O.M. & Bäck, T.
In M. Affenzeller M., et al. Rds.), Parallel Problem Solving from Nature: Lecture Notes in Computer Science. Springer, Cham
2024
Multi-Objective Mixed-Integer Quadratic Models: A Study on Mathematical Programming and Evolutionary Computation
Ofer M. Shir and Michael Emmerich
This paper appears in: IEEE Transactions on Evolutionary Computation On page(s): 1-15 Print ISSN: 1089-778X Online ISSN: 1941-0026 Digital Object Identifier: 10.1109/TEVC.2024.3374519
2024
Towards AI Research Agents in the Chemical Sciences
Ofer M. Shir
ChemRxiv. Cambridge: Cambridge Open Engage; 2024
2024
On the Behavior of the Mixed-Integer SMS-EMOA on Box-Constrained Quadratic Bi-Objective Models
Shir, O.M., Emmerich, M.
2023
Saliency Can Be All You Need In Contrastive Self-Supervised Learning
Kocaman, V., Shir, O.M., Bäck, T., Belbachir, A.N.
2022
Toward an ImageNet Library of Functions for Global Optimization Benchmarking
Yazmir B., Shir, O.M.
arXiv preprint (2022)
2022
Algorithmically-guided postharvest by experimental combinatorial optimization
Shir, O.M., Yazmir, B., Israeli, A., Gamrasni, D.
Proceedings of the Genetic and Evolutionary Computation Conference Companion, GECCO-2022, New York, NY, USA, ACM Press (2022) 2027–2035
2022
Algorithmically-guided discovery of viral epitopes via linguistic parsing: Problem formulation and solving by soft computing
Shir, O.M., Israeli, A., Caftory, A., Zepko, G., Bloch, I.
Applied Soft Computing, Volume 129 (2022) 109509
2022
Introductory Mathematical Programming for EC
Shir, O.M.
Proceedings of the Genetic and Evolutionary Computation Conference Companion, GECCO-2022, New York, NY, USA, ACM Press (2022)
2022
Sequential Experimentation by Evolutionary Algorithms
Shir, O.M., Bäck, T.
Proceedings of the Genetic and Evolutionary Computation Conference Companion, GECCO-2022, New York, NY, USA, ACM Press (2022)
2022
The Unreasonable Effectiveness of the Final Batch Normalization Layer
Kocaman, V., Shir, O.M., Bäck, T.
Proceedings of the 16th International Symposium on Visual Computing, ISVC'21
2021
Locating the local minima in lens design with machine learning
Kononova, A.V., Shir, O.M., Tukker, T., Frisco, P., Zeng, S., Bäck, T.
Current Developments in Lens Design and Optical Engineering XXII 11814, 1181402
2021
Automated Feature Detection of Black-Box Continuous Search-Landscapes using Neural Image Recognition
Yazmir, B., Shir, O.M.
Proceedings of the Genetic and Evolutionary Computation Conference Companion, GECCO-2021, New York, NY, USA, ACM Press (2021) 213–214
2021
Addressing the Multiplicity of Solutions in Optical Lens Design as a Niching Evolutionary Algorithms Computational Challenge
Kononova, A.V., Shir, O.M., Tukker, T., Frisco, P., Zeng, S., Bäck, T.
Proceedings of the Genetic and Evolutionary Computation Conference Companion, GECCO-2021, New York, NY, USA, ACM Press (2021) 1596–1604
2021
Multi-level evolution strategies for high-resolution black-box control
Shir, O.M., Xi, X., Rabitz, H.
Journal of Heuristics (2021), Springer US
2021
Improving Model Accuracy for Imbalanced Image Classification Tasks by Adding a Final Batch Normalization Layer: An Empirical Study
Kocaman, V., Shir, O.M., Bäck, T.
Proceedings of the 25th International Conference on Pattern Recognition, ICPR2020 (2021) 10404–10411
2021
On the Covariance-Hessian Relation in Evolution Strategies.
Shir, O.M., Yehudayoff, A.
Theoretical Computer Science 801 (2020) 157—174
2020
Benchmarking Discrete Optimization Heuristics with IOHprofiler.
Doerr, C., Ye, F., Horesh, N., Wang, H., Shir, O.M., Bäck, T.
Applied Soft Computing 88 (2020) 106027
2020
Predict or Screen Your Expensive Assay? DoE vs. Surrogates in Experimental Combinatorial Optimization.
Horesh, N., Bäck, T., Shir, O.M.
In Proceedings of the Genetic and Evolutionary Computation Conference, GECCO-2019 ,2019, Ed. ,ACM Press New York, NY, USA, Pages 274?284
2019
Statistical Learning in Soil Sampling Design Aided by Pareto Optimization.
Israeli, A., Emmerich, M., Litaor, M., Shir, O.M.
In Proceedings of the Genetic and Evolutionary Computation Conference, GECCO-2019 ,2019, Ed. ,ACM Press New York, NY, USA, Pages 1198?1205
2019
Bayesian Performance Analysis for Black-Box Optimization Benchmarking.
Calvo, B., Shir, O.M., Ceberio, J., Doerr, C., Wang, H., Bäck, T., Lozano, J.A.
In Proceedings of the Genetic and Evolutionary Computation Conference Companion, GECCO-2019 ,2019, Ed. ,ACM Press New York, NY, USA, Pages 1789?1797
2019
Evolution Strategies.
Emmerich, M.T.M., Shir, O.M., Wang, H.
In Handbook of Heuristics. ,2018, Martí R., Panos P., Resende M. Ed. ,Springer Cham , Pages 1-31
2018
Compiling A Benchmarking Test-Suite For Combinatorial Black-Box Optimization: A Position Paper.
Shir, O.M., Doerr, C., Bäck, T.
In Proceedings of the Genetic and Evolutionary Computation Conference Companion, GECCO-2018 ,2018, ACM Press Ed. , New York, NY, USA,, Pages 1753?1760
2018
On the Statistical Learning Ability of Evolution Strategies
Shir, O.M., Yehudayoff, A.
In Proceedings of the 14th ACM/SIGEVO Conference on Foundations of Genetic Algorithms FOGA-2017 ,2017, ACM Press Ed. ,ACM Press New York, NY, US, Pages 127?138
2017