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Deep statistics: more robust performance statistics for single-objective optimization benchmarking.

, , , , , and . GECCO Companion, page 5-6. ACM, (2020)

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Four algorithms to solve symmetric multi-type non-negative matrix tri-factorization problem., , , , , , and . CoRR, (2020)Dealing with zero-inflated data: achieving SOTA with a two-fold machine learning approach., , , , , , , and . CoRR, (2023)On Suitability of the Customized Measuring Device for Electric Motor., , , , , and . IECON, page 1-6. IEEE, (2022)How Far Out of Distribution Can We Go With ELA Features and Still Be Able to Rank Algorithms?, and . SSCI, page 341-346. IEEE, (2023)TinyTLA: Topological landscape analysis for optimization problem classification in a limited sample setting., , and . Swarm Evol. Comput., (February 2024)TLA: Topological Landscape Analysis for Single-Objective Continuous Optimization Problem Instances., , and . SSCI, page 1698-1705. IEEE, (2022)Four algorithms to solve symmetric multi-type non-negative matrix tri-factorization problem., , , , , , and . J. Glob. Optim., 82 (2): 283-312 (2022)Deep statistics: more robust performance statistics for single-objective optimization benchmarking., , , , , and . GECCO Companion, page 5-6. ACM, (2020)Less is more: Selecting the right benchmarking set of data for time series classification., , , , , , and . Expert Syst. Appl., (2022)Preferred Solutions of the Ground Station Scheduling Problem using NSGA-III with Weighted Reference Points Selection., , and . CEC, page 1840-1847. IEEE, (2021)