63 citations · 151 across the 18 of their papers we have counts for
21 papers
The Quantum Sphere: A Physically Realizable Optimization Benchmark with Provable Linear Convergence in White- and Black-Box Settings
Ofer M. Shir
We revisit an established Quantum Control objective, characterize its exact local metric geometry, and reposition it as a rigorous benchmark for Search and Optimization. The trap-f…
Integer Natural Evolution Strategies
Jacob de Nobel, Diederick Vermetten, Hao Wang +3
While contemporary Evolution Strategies handle integer optimization problems effectively, their adaptation mechanism is grounded in -based Gaussian models, which are not na…
Correlated Mutations for Integer Programming
Ofer M. Shir, Michael Emmerich
Even with the recent theoretical advancements that dramatically reduced the complexity of Integer Programming (IP), heuristics remain the dominant problem-solvers for this difficul…
Avoiding Redundant Restarts in Multimodal Global Optimization
Jacob de Nobel, Diederick Vermetten, Anna V. Kononova +2
Naïve restarts of global optimization solvers when operating on multimodal search landscapes may resemble the Coupon's Collector Problem, with a potential to waste significant func…
Addressing Unboundedness in Quadratically-Constrained Mixed-Integer Problems
Guy Zepko, Ofer M. Shir
Mixed-integer (MI) quadratic models subject to quadratic constraints, known as All-Quadratic MI Programs, constitute a challenging class of NP-complete optimization problems. The p…
Physics-Guided Inverse Regression for Crop Quality Assessment
David Shulman, Assaf Israeli, Yael Botnaro +6
We present an innovative approach leveraging Physics-Guided Neural Networks (PGNNs) for enhancing agricultural quality assessments. Central to our methodology is the application of…
Lessons Learned Report: Super-Resolution for Detection Tasks in Engineering Problem-Solving
Martin Feder, Michal Horovitz, Assaf Chen +2
We describe the lessons learned from targeting agricultural detection problem-solving, when subject to low resolution input maps, by means of Machine Learning-based super-resolutio…
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…
Toward an ImageNet Library of Functions for Global Optimization Benchmarking
Boris Yazmir, Ofer M. Shir
Knowledge of search-landscape features of BlackBox Optimization (BBO) problems offers valuable information in light of the Algorithm Selection and/or Configuration problems. Explor…
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…
On the Covariance-Hessian Relation in Evolution Strategies
Ofer M. Shir, Amir Yehudayoff
We consider Evolution Strategies operating only with isotropic Gaussian mutations on positive quadratic objective functions, and investigate the covariance matrix when constructed…
On the Theoretical Capacity of Evolution Strategies to Statistically Learn the Landscape Hessian
Ofer M. Shir, Jonathan Roslund, Amir Yehudayoff
We study the theoretical capacity to statistically learn local landscape information by Evolution Strategies (ESs). Specifically, we investigate the covariance matrix when construc…
Exploring the complexity of quantum control optimization trajectories
Arun Nanduri, Ofer M. Shir, Ashley Donovan +2
The control of quantum system dynamics is generally performed by seeking a suitable applied field. The physical objective as a functional of the field forms the quantum control lan…
Quantum Control Experiments as a Testbed for Evolutionary Multi-Objective Algorithms
Ofer M. Shir, Jonathan Roslund, Zaki Leghtas +1
Experimental multi-objective Quantum Control is an emerging topic within the broad physics and chemistry applications domain of controlling quantum phenomena. This realm offers cut…
Evolutionary Hessian Learning: Forced Optimal Covariance Adaptive Learning (FOCAL)
Ofer M. Shir, Jonathan Roslund, Darrell Whitley +1
The Covariance Matrix Adaptation Evolution Strategy (CMA-ES) has been the most successful Evolution Strategy at exploiting covariance information; it uses a form of Principle Compo…
Fidelity Between Unitary Operators and the Generation of Gates Robust Against Off-Resonance Perturbations
Renan Cabrera, Ofer M. Shir, Rebing Wu +1
We perform a functional expansion of the fidelity between two unitary matrices in order to find the necessary conditions for the robust implementation of a target gate. Comparison…
Control of quantum dynamics by optimized measurements
Feng Shuang, Mianlai Zhou, Alexander Pechen +3
Quantum measurements are considered for optimal control of quantum dynamics with instantaneous and continuous observations utilized to manipulate population transfer. With an optim…