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2020 – today
- 2024
[j10]Mitra Baratchi, Can Wang, Steffen Limmer, Jan N. van Rijn, Holger H. Hoos, Thomas Bäck, Markus Olhofer:
Automated machine learning: past, present and future. Artif. Intell. Rev. 57(5): 122 (2024)- [c26]Angus Kenny
, Tapabrata Ray, Steffen Limmer, Hemant Kumar Singh, Tobias Rodemann, Markus Olhofer:
A Hierarchical Dissimilarity Metric for Automated Machine Learning Pipelines, and Visualizing Search Behaviour. EvoApplications@EvoStar 2024: 115-129 - [c25]Maria Bresich, Günther R. Raidl, Steffen Limmer:
Letting a Large Neighborhood Search for an Electric Dial-A-Ride Problem Fly: On-The-Fly Charging Station Insertion. GECCO 2024 - [c24]Angus Kenny, Tapabrata Ray, Steffen Limmer, Hemant Kumar Singh, Tobias Rodemann, Markus Olhofer:
Using Bayesian Optimization to Improve Hyperparameter Search in TPOT. GECCO 2024 - [i11]Steffen Limmer, Steffen Udluft, Clemens Otte:
Neural-ANOVA: Model Decomposition for Interpretable Machine Learning. CoRR abs/2408.12319 (2024) - 2023
- [c23]Steffen Limmer, Johannes Varga, Günther R. Raidl:
An Evolutionary Approach for Scheduling a Fleet of Shared Electric Vehicles. EvoApplications@EvoStar 2023: 3-18 - [c22]Angus Kenny, Tapabrata Ray, Steffen Limmer, Hemant Kumar Singh, Tobias Rodemann, Markus Olhofer:
Hybridizing TPOT with Bayesian Optimization. GECCO 2023: 502-510 - [c21]Steffen Limmer, Alberto Martínez Alba, Nicola Michailow:
Physics-Informed Neural Networks for Pathloss Prediction. MLSP 2023: 1-5 - [c20]Margarita Veshchezerova, Mikhail Somov, David Bertsche, Steffen Limmer, Sebastian Schmitt, Michael Perelshtein, Ayush Joshi Tripathi:
A Hybrid Quantum-Classical Approach to the Electric Mobility Problem. QCE 2023: 636-641 - [i10]Direnc Pekaslan, Jose Maria Alonso-Moral, Kasun Bandara, Christoph Bergmeir, Juan Bernabé-Moreno, Robert Eigenmann, Nils Einecke, Selvi Ergen, Rakshitha Godahewa, Hansika Hewamalage, Jesus Lago, Steffen Limmer, Sven Rebhan, Boris Rabinovich, Dilini Rajapaksha, Heda Song, Christian Wagner, Wenlong Wu, Luis Magdalena, Isaac Triguero:
The Energy Prediction Smart-Meter Dataset: Analysis of Previous Competitions and Beyond. CoRR abs/2311.04007 (2023) - 2022
- [j9]Johannes Varga, Günther R. Raidl, Steffen Limmer:
Computational Methods for Scheduling the Charging and Assignment of an On-Site Shared Electric Vehicle Fleet. IEEE Access 10: 105786-105806 (2022) - [j8]Hemant Kumar Singh, Tapabrata Ray, Md Juel Rana, Steffen Limmer, Tobias Rodemann, Markus Olhofer:
Investigating the Use of Linear Programming and Evolutionary Algorithms for Multi-Objective Electric Vehicle Charging Problem. IEEE Access 10: 115322-115337 (2022) - [i9]Steffen Limmer, Alberto Martínez Alba, Nicola Michailow:
Physics-informed neural networks for pathloss prediction. CoRR abs/2211.12986 (2022) - [i8]Christoph Bergmeir, Frits de Nijs, Abishek Sriramulu, Mahdi Abolghasemi, Richard Bean, John M. Betts, Quang Bui, Nam Trong Dinh, Nils Einecke, Rasul Esmaeilbeigi, Scott Ferraro, Priya Galketiya, Evgenii Genov, Robert Glasgow, Rakshitha Godahewa, Yanfei Kang, Steffen Limmer, Luis Magdalena, Pablo Montero-Manso, Daniel Peralta, Yogesh Pipada Sunil Kumar, Alejandro Rosales-Pérez, Julian Ruddick, Akylas C. Stratigakos, Peter J. Stuckey, Guido Tack, Isaac Triguero, Rui Yuan:
Comparison and Evaluation of Methods for a Predict+Optimize Problem in Renewable Energy. CoRR abs/2212.10723 (2022) - 2021
- [j7]Steffen Limmer, Fernando Lezama, João P. Soares, Zita A. Vale:
Coordination of Home Appliances for Demand Response: An Improved Optimization Model and Approach. IEEE Access 9: 146183-146194 (2021) - [j6]Yali Wang, Steffen Limmer, Markus Olhofer, Michael Emmerich, Thomas Bäck:
Automatic preference based multi-objective evolutionary algorithm on vehicle fleet maintenance scheduling optimization. Swarm Evol. Comput. 65: 100933 (2021) - [c19]Van Duc Nguyen, Ewout Zwanenburg, Steffen Limmer, Wessel Luijben, Thomas Bäck, Markus Olhofer:
A Combination of Fourier Transform and Machine Learning for Fault Detection and Diagnosis of Induction Motors. DSA 2021: 344-351 - [i7]Yali Wang, Steffen Limmer, Markus Olhofer, Michael Emmerich, Thomas Bäck:
Automatic Preference Based Multi-objective Evolutionary Algorithm on Vehicle Fleet Maintenance Scheduling Optimization. CoRR abs/2101.09556 (2021) - 2020
- [c18]Takahiro Ishihara, Steffen Limmer:
Optimizing the Hyperparameters of a Mixed Integer Linear Programming Solver to Speed up Electric Vehicle Charging Control. EvoApplications 2020: 37-53 - [i6]Daniel Hein, Steffen Limmer, Thomas A. Runkler:
Interpretable Control by Reinforcement Learning. CoRR abs/2007.09964 (2020)
2010 – 2019
- 2019
- [c17]Yali Wang, Steffen Limmer, Markus Olhofer, Michael T. M. Emmerich, Thomas Bäck:
Vehicle Fleet Maintenance Scheduling Optimization by Multi-objective Evolutionary Algorithms. CEC 2019: 442-449 - [c16]Marios Kefalas, Steffen Limmer, Asteris Apostolidis, Markus Olhofer, Michael Emmerich, Thomas Bäck:
A tabu search-based memetic algorithm for the multi-objective flexible job shop scheduling problem. GECCO (Companion) 2019: 1254-1262 - [c15]Can Wang, Thomas Bäck, Holger H. Hoos, Mitra Baratchi, Steffen Limmer, Markus Olhofer:
Automated Machine Learning for Short-term Electric Load Forecasting. SSCI 2019: 314-321 - 2018
- [j5]Steffen Limmer, Slawomir Stanczak:
A Neural Architecture for Bayesian Compressive Sensing Over the Simplex via Laplace Techniques. IEEE Trans. Signal Process. 66(22): 6002-6015 (2018) - [c14]Miruna Raceala-Motoc, Steffen Limmer, Igor Bjelakovic, Slawomir Stanczak:
Distributed Machine Learning in the Context of Function Computation over Wireless Networks. ACSSC 2018: 291-297 - [c13]Steffen Limmer, Tobias Rodemann:
Robust Evolutionary Optimization Based on Coevolution. EvoApplications 2018: 813-831 - [c12]Steffen Limmer, Manuel Dietrich:
Optimization of Dynamic Prices for Electric Vehicle Charging Considering Fairness. SSCI 2018: 2304-2311 - 2017
- [j4]Steffen Limmer, Dietmar Fey:
Comparison of common parallel architectures for the execution of the island model and the global parallelization of evolutionary algorithms. Concurr. Comput. Pract. Exp. 29(9) (2017) - [c11]Steffen Limmer, Tobias Rodemann:
Multi-objective optimization of plug-in electric vehicle charging prices. SSCI 2017: 1-8 - [i5]Steffen Limmer, Slawomir Stanczak:
Optimal deep neural networks for sparse recovery via Laplace techniques. CoRR abs/1709.01112 (2017) - 2016
- [c10]Steffen Limmer, Dietmar Fey:
Investigation of strategies for an increasing population size in multi-objective CMA-ES. CEC 2016: 476-483 - [c9]Steffen Limmer, Slawomir Stanczak:
Towards optimal nonlinearities for sparse recovery using higher-order statistics. MLSP 2016: 1-6 - [i4]Steffen Limmer, Slawomir Stanczak:
Towards optimal nonlinearities for sparse recovery using higher-order statistics. CoRR abs/1605.08201 (2016) - 2015
- [b1]Steffen Limmer:
Vergleich gebräuchlicher Parallelrechensysteme für die Beschleunigung evolutionärer Algorithmen demonstriert für den Entwurf miniaturisierter optischer und elektronischer Bauelemente. University of Erlangen-Nuremberg, 2015 - [c8]Steffen Limmer, Jafar Mohammadi, Slawomir Stanczak:
A simple algorithm for approximation by nomographic functions. Allerton 2015: 453-458 - [i3]Steffen Limmer, Jafar Mohammadi, Slawomir Stanczak:
A Simple Algorithm for Approximation by Nomographic Functions. CoRR abs/1504.05474 (2015) - 2014
- [j3]Steffen Limmer, André Schneider, Christian Boehme, Dietmar Fey, Simon Schmitz, Achim Graupner, Martin Sülzle:
Services for numerical simulations and optimisations in grids. Int. J. Parallel Emergent Distributed Syst. 29(6): 521-543 (2014) - [c7]Steffen Limmer, Maik Srba, Dietmar Fey:
Performance Investigation and Tuning in the Interoperable Cloud4E Platform. Euro-Par Workshops (2) 2014: 85-96 - [c6]Steffen Limmer, Slawomir Stanczak:
On ℓp-norm computation over multiple-access channels. ITW 2014: 351-355 - [i2]Steffen Limmer, Slawomir Stanczak:
On ℓp-norm Computation over Multiple-Access Channels. CoRR abs/1409.1122 (2014) - 2013
- [j2]Johannes Hofmann, Steffen Limmer, Dietmar Fey:
Performance investigations of genetic algorithms on graphics cards. Swarm Evol. Comput. 12: 33-47 (2013) - [c5]Steffen Limmer, Slawomir Stanczak, Mario Goldenbaum, Renato L. G. Cavalcante:
Exploiting interference for efficient distributed computation in cluster-based wireless sensor networks. GlobalSIP 2013: 933-936 - [i1]Steffen Limmer, Slawomir Stanczak, Mario Goldenbaum, Renato L. G. Cavalcante:
Exploiting Interference for Efficient Distributed Computation in Cluster-based Wireless Sensor Networks. CoRR abs/1309.3139 (2013) - 2012
- [c4]Steffen Limmer, Dietmar Fey, Ulrich Lohmann, Jürgen Jahns:
Evolutionary Design of Active Free Space Optical Networks Based on Digital Mirror Devices. EvoApplications 2012: 21-30 - 2011
- [c3]Steffen Limmer, Dietmar Fey, Ulrich Lohmann, Jürgen Jahns:
Evolutionary optimization of layouts for high density free space optical network links. GECCO 2011: 1635-1642 - 2010
- [j1]Dietmar Fey, Steffen Limmer:
Unconventional Computing - Reversible Signed Digit Adders for Future Nanocomputing Devices (Unkonventionelles Rechnen - reversible Addierer für künftiges Nanocomputing). it Inf. Technol. 52(3): 147-152 (2010) - [c2]Steffen Limmer, Dietmar Fey:
Framework for Distributed Evolutionary Algorithms in Computational Grids. ISICA (1) 2010: 170-180 - [c1]Ulrich Lohmann, Jürgen Jahns, Steffen Limmer, Dietmar Fey:
Simulation and Optimized Design of High Density Optical Crossconnect Systems for Massively Parallel Computing Architectures. OSC 2010: 42-52
Coauthor Index
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last updated on 2024-09-30 00:10 CEST by the dblp team
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