2 papers
cs.LG2026
Learning to Assess the Reliability of Number-of-Runs Estimation in Stochastic Optimization
Sara Gjorgjieva, Eva Tuba, Tome Eftimov
In large-scale benchmarking of stochastic optimization algorithms, the key challenge is no longer whether repeated runs are needed for reliability, but how to determine when suffic…
cs.NE2026
On the Structural (Dis)Agreement of Landscape Representations in Black-Box Optimization
Sara Gjorgjieva, Eva Tuba, Barbara Koroušić Seljak +2
Landscape feature representations play a central role in automated algorithm selection and meta-learning for black-box optimization, yet little is known about how different represe…