40 citations · 54 across the 7 of their papers we have counts for
10 papers
Saliency Can Be All You Need In Contrastive Self-Supervised Learning
Veysel Kocaman, Ofer M. Shir, Thomas Bäck +1
We propose an augmentation policy for Contrastive Self-Supervised Learning (SSL) in the form of an already established Salient Image Segmentation technique entitled Global Contrast…
The Unreasonable Effectiveness of the Final Batch Normalization Layer
Veysel Kocaman, Ofer M. Shir, Thomas Baeck
Early-stage disease indications are rarely recorded in real-world domains, such as Agriculture and Healthcare, and yet, their accurate identification is critical in that point of t…
Addressing the Multiplicity of Solutions in Optical Lens Design as a Niching Evolutionary Algorithms Computational Challenge
Anna V. Kononova, Ofer M. Shir, Teus Tukker +3
Optimal Lens Design constitutes a fundamental, long-standing real-world optimization challenge. Potentially large number of optima, rich variety of critical points, as well as soli…
Improving Model Accuracy for Imbalanced Image Classification Tasks by Adding a Final Batch Normalization Layer: An Empirical Study
Veysel Kocaman, Ofer M. Shir, Thomas Bäck
Some real-world domains, such as Agriculture and Healthcare, comprise early-stage disease indications whose recording constitutes a rare event, and yet, whose precise detection at…
Multi-Level Evolution Strategies for High-Resolution Black-Box Control
Ofer M. Shir, Xi Xing, Herschel Rabitz
This paper introduces a multi-level (m-lev) mechanism into Evolution Strategies (ESs) in order to address a class of global optimization problems that could benefit from fine discr…
Benchmarking Discrete Optimization Heuristics with IOHprofiler
Carola Doerr, Furong Ye, Naama Horesh +3
Automated benchmarking environments aim to support researchers in understanding how different algorithms perform on different types of optimization problems. Such comparisons provi…