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20232025
most citedBenchmarking Algorithms for Submodular Optimization Problems Using IOHProfiler

1 citations · 1 across the 5 of their papers we have counts for

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5 papers

cs.SD2025

From Spikes to Speech: NeuroVoc -- A Biologically Plausible Vocoder Framework for Auditory Perception and Cochlear Implant Simulation

Jacob de Nobel, Jeroen J. Briaire, Thomas H. W. Baeck +2

We present NeuroVoc, a flexible model-agnostic vocoder framework that reconstructs acoustic waveforms from simulated neural activity patterns using an inverse Fourier transform. Th…

cs.NE2024

MO-IOHinspector: Anytime Benchmarking of Multi-Objective Algorithms using IOHprofiler

Diederick Vermetten, Jeroen Rook, Oliver L. Preuß +5

Benchmarking is one of the key ways in which we can gain insight into the strengths and weaknesses of optimization algorithms. In sampling-based optimization, considering the anyti…

cs.NE2023

When to be Discrete: Analyzing Algorithm Performance on Discretized Continuous Problems

André Thomaser, Jacob de Nobel, Diederick Vermetten +3

The domain of an optimization problem is seen as one of its most important characteristics. In particular, the distinction between continuous and discrete optimization is rather im…

cs.NE2023

Towards Self-adaptive Mutation in Evolutionary Multi-Objective Algorithms

Furong Ye, Frank Neumann, Jacob de Nobel +2

Parameter control has succeeded in accelerating the convergence process of evolutionary algorithms. While empirical and theoretical studies have shed light on the behavior of algor…

cs.AI20231 cited

Benchmarking Algorithms for Submodular Optimization Problems Using IOHProfiler

Frank Neumann, Aneta Neumann, Chao Qian +7

Submodular functions play a key role in the area of optimization as they allow to model many real-world problems that face diminishing returns. Evolutionary algorithms have been sh…