Ana Nikolikj

Orcid: 0000-0002-6983-9627

According to our database1, Ana Nikolikj authored at least 14 papers between 2022 and 2024.

Collaborative distances:

Timeline

2022
2023
2024
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Bibliography

2024
A Learning Search Algorithm for the Restricted Longest Common Subsequence Problem.
CoRR, 2024

A Survey of Meta-features Used for Automated Selection of Algorithms for Black-box Single-objective Continuous Optimization.
CoRR, 2024

Comparing Solvability Patterns of Algorithms across Diverse Problem Landscapes.
Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2024

Instance Selection for Dynamic Algorithm Configuration with Reinforcement Learning: Improving Generalization.
Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2024

Quantifying Individual and Joint Module Impact in Modular Optimization Frameworks.
Proceedings of the IEEE Congress on Evolutionary Computation, 2024

Generalization Ability of Feature-Based Performance Prediction Models: A Statistical Analysis Across Benchmarks.
Proceedings of the IEEE Congress on Evolutionary Computation, 2024

2023
Algorithm Instance Footprint: Separating Easily Solvable and Challenging Problem Instances.
Proceedings of the Genetic and Evolutionary Computation Conference, 2023

Assessing the Generalizability of a Performance Predictive Model.
Proceedings of the Companion Proceedings of the Conference on Genetic and Evolutionary Computation, 2023

RF+clust for Leave-One-Problem-Out Performance Prediction.
Proceedings of the Applications of Evolutionary Computation - 26th European Conference, 2023

Sensitivity Analysis of RF+clust for Leave-One-Problem-Out Performance Prediction.
Proceedings of the IEEE Congress on Evolutionary Computation, 2023

PS-AAS: Portfolio Selection for Automated Algorithm Selection in Black-Box Optimization.
Proceedings of the International Conference on Automated Machine Learning, 2023

2022
Improving Nevergrad's Algorithm Selection Wizard NGOpt Through Automated Algorithm Configuration.
Proceedings of the Parallel Problem Solving from Nature - PPSN XVII, 2022

Identifying minimal set of Exploratory Landscape Analysis features for reliable algorithm performance prediction.
Proceedings of the IEEE Congress on Evolutionary Computation, 2022

Explaining Differential Evolution Performance Through Problem Landscape Characteristics.
Proceedings of the Bioinspired Optimization Methods and Their Applications, 2022


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