Nico Strasdat
Research Associate
NameDr. Nico Strasdat
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Visiting address:
Willersbau, Room C 39 Zellescher Weg 12-14
01069 Dresden
Teaching
You can find information about my teaching activities here.
Scientific Interests
- Methods for machine learning, in particular Support Vector Machines and Deep Learning
- Application of convex optimization and duality
- Newton-type methods for the solution of optimization problems
- Integer-linear programming
- Treatment of application-related optimization problems
- Effective and efficient implementation of algorithms
Short CV
- Doctor rerum naturalium in Mathematics (10/2014 to 10/2023), Dissertation: "Duality, Derivative-Based Training Methods and Hyperparameter Optimization for Support Vector Machines"
- Master of Science (Mathematik) at Technische Universität Dresden (10/2012 to 09/2014), Master's Thesis: "Reduced-Set Support Vector Machines"
- Bachelor of Science (Mathematik) at Technische Universität Dresden (10/2009 to 08/2012), Bachelor's Thesis: "Random Forests und ihre Anwendung zur Regression"
Publications
2024
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Worst-case analysis of heuristic approaches for the temporal bin packing problem with fire-ups, Feb 2024, 333, 1, p. 481-499, 19 p.Electronic (full-text) versionResearch output: Contribution to journal > Research article
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Theoretical Insights and a New Class of Valid Inequalities for the Temporal Bin Packing Problem with Fire-Ups, 2024, 44, 26 p., e283503Electronic (full-text) versionResearch output: Contribution to journal > Research article
2023
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Solving the Skiving Stock Problem by a Combination of Stabilized Column Generation and the Reflect Arc-Flow Model, 31 Jul 2023, 334, p. 145-162, 18 p.Electronic (full-text) versionResearch output: Contribution to journal > Research article
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A Combinatorial Flow-based Formulation for Temporal Bin Packing Problems, 2023, 307(2), p. 554-574, 21 p.Electronic (full-text) versionResearch output: Contribution to journal > Research article
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A Heuristic Column Generation Approach for the Stochastic Bin Packing Problem, 2023, Operations Research Proceedings 2022. p. 131-138, 8 p.Electronic (full-text) versionResearch output: Contribution to book/conference proceedings/anthology/report > Conference contribution
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An extended convergence framework applied to complementarity systems with degenerate and nonisolated solutions, 2023, 8, 4, p. 1039-1054Electronic (full-text) versionResearch output: Contribution to journal > Research article
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Duality, Derivative-Based Training Methods and Hyperparameter Optimization for Support Vector Machines, 2023Electronic (full-text) versionResearch output: Types of Thesis > Doctoral thesis
2022
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A Heuristic-based Reduction for the Temporal Bin Packing Problem with Fire-Ups, 2022, Operations Research Proceedings 2021. p. 127-133, 7 p.Research output: Contribution to book/conference proceedings/anthology/report > Conference contribution
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Variable and constraint reduction techniques for the temporal bin packing problem with fire-ups, 2022, 2022, 16, p. 2333-2358, 26 p.Electronic (full-text) versionResearch output: Contribution to journal > Research article
2021
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Compact Integer Linear Programming Formulations for the Temporal Bin Packing Problem with Fire-Ups, Aug 2021, 132, 132, 105288Electronic (full-text) versionResearch output: Contribution to journal > Research article
2020
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Improved Flow-based Formulations for the Skiving Stock Problem, 2020, 113, 104770Research output: Contribution to journal > Research article
2019
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A special complementarity function revisited, 2019, 68, 1, p. 65-79Electronic (full-text) versionResearch output: Contribution to journal > Research article
2015
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Efficient optimization of hyper-parameters for least-squares support vector regression, 2015, 30, p. 1095-1108, 14 p.Electronic (full-text) versionResearch output: Contribution to journal > Research article
This information is provided by the FIS.
Recent and current projects
- Datengetriebene Generierung von Modellen und Sensitivitätsanalyse für Produktionsprozesse (BMBF, 04/2020 to 11/2023) im Verbundprojekt OptProDat
- Anspruchsvolle Freiformbeschichtung flächiger und 3-dimensionaler Substrate durch Inline-Sputtertechnick (SAB, 08/2019 to 12/2020)
- Newton-type Methods for Nonsmooth Equations with Nonisolated Solutions (DFG, 01/2017 to 12/2019)
- Optimierungstechniken für Klassifikation und Regression, Teil II (Industry, 01/2017 to 12/2017)
- Optimierungstechniken für Klassifikation und Regression (Industry, 10/2014 to 12/2016)
- Support-Vector-Methoden und multivariate Regression (Industry, 04/2013 to 09/2014)
- Support Vector Methoden (Industry, 09/2011 to 08/2013)