Computational Intelligence

Prof. Ofer Shir

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

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

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

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

Protein Design by Multiobjective Optimization: Evolutionary and Non-Evolutionary Approaches.

Belure, S.V., Shir, O.M., Nanda, V.
In Proceedings of the Genetic and Evolutionary Computation Conference, GECCO-2017 ,2017, Ed. ,ACM Press New York, USA, Pages 1081?1088
2017

Searching for the Pareto frontier in multi-objective protein design.

Nanda, V., Belure, S.V., Shir, O.M.
Biophysical Reviews 2017 Volume 9 Issue 4 Pages 339?344
2017

Solving Structures of Pigment-Protein Complexes as Inverse Optimization Problems using Decomposition.

Lahav, Y., Shir, O.M., Noy, D.
In Proceedings of the Genetic and Evolutionary Computation Conference, GECCO-2017, ,2017, Ed. ,ACM Press New York, NY, USA,, Pages 1169?1176
2017