Manuel Schmitt

Ingo Krossing

J. Comput. Chem., January, 2023

2022

Exact Markov chain-based runtime analysis of a discrete particle swarm optimization algorithm on sorting and OneMax.

[BibT_eX]

[DOI]

Nat. Comput., 2022

ORCA-WHISPER: An Automatic Killer Whale Sound Type Generation Toolkit Using Deep Learning.

[BibT_eX]

[DOI]

Proceedings of the 23rd Annual Conference of the International Speech Communication Association, 2022

ORCA-PARTY: An Automatic Killer Whale Sound Type Separation Toolkit Using Deep Learning.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Acoustics, 2022

2021

ORCA-SLANG: An Automatic Multi-Stage Semi-Supervised Deep Learning Framework for Large-Scale Killer Whale Call Type Identification.

[BibT_eX]

[DOI]

Proceedings of the 22nd Annual Conference of the International Speech Communication Association, Interspeech 2021, Brno, Czechia, August 30, 2021

2020

Self-adaptive potential-based stopping criteria for Particle Swarm Optimization with forced moves.

[BibT_eX]

[DOI]

Swarm Intell., 2020

ORCA-CLEAN: A Deep Denoising Toolkit for Killer Whale Communication.

[BibT_eX]

[DOI]

Proceedings of the 21st Annual Conference of the International Speech Communication Association, 2020

2019

Theory of particle swarm optimization: A survey of the power of the swarm's potential.

[BibT_eX]

[DOI]

Alexander Raß

it Inf. Technol., 2019

Self-adaptive Potential-based Stopping Criteria for Particle Swarm Optimization.

[BibT_eX]

[DOI]

CoRR, 2019

Deep Representation Learning for Orca Call Type Classification.

[BibT_eX]

[DOI]

Proceedings of the Text, Speech, and Dialogue - 22nd International Conference, 2019

Deep Learning for Orca Call Type Identification - A Fully Unsupervised Approach.

[BibT_eX]

[DOI]

Proceedings of the 20th Annual Conference of the International Speech Communication Association, 2019

2017

Runtime Analysis of a Discrete Particle Swarm Optimization Algorithm on Sorting and OneMax.

[BibT_eX]

[DOI]

Proceedings of the 14th ACM/SIGEVO Conference on Foundations of Genetic Algorithms, 2017

2015

Particle swarm optimization almost surely finds local optima.

[BibT_eX]

[DOI]

Theor. Comput. Sci., 2015

Konvergenzanalyse für die Partikelschwarmoptimierung.

[BibT_eX]

[DOI]

Proceedings of the Ausgezeichnete Informatikdissertationen 2015, 2015

Explanation of Stagnation at Points that are not Local Optima in Particle Swarm Optimization by Potential Analysis.

[BibT_eX]

[DOI]

Alexander Raß

Proceedings of the Genetic and Evolutionary Computation Conference, 2015

Multimodal medical image registration using particle swarm optimization with influence of the data's initial orientation.

[BibT_eX]

[DOI]

Lydia Schwab

Proceedings of the IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, 2015

2014

How Much Forcing Is Necessary to Let the Results of Particle Swarms Converge?

[BibT_eX]

[DOI]

Proceedings of the Swarm Intelligence Based Optimization - First International Conference, 2014

Towards a Better Understanding of the Local Attractor in Particle Swarm Optimization: Speed and Solution Quality.

[BibT_eX]

[DOI]

Vanessa Lange

Proceedings of the Adaptive and Intelligent Systems - Third International Conference, 2014

2013

Exploiting independent subformulas: A faster approximation scheme for #k-SAT.

[BibT_eX]

[DOI]

Inf. Process. Lett., 2013

Particles prefer walking along the axes: experimental insights into the behavior of a particle swarm.

[BibT_eX]

[DOI]