Maximilian Thiessen

According to our database, Maximilian Thiessen authored at least 16 papers between 2020 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2025

Efficient Algorithms for Learning and Compressing Monophonic Halfspaces in Graphs.

Marco Bressan, Victor Chepoi, Emmanuel Esposito, Maximilian Thiessen

CoRR, June, 2025

Maximally Expressive GNNs for Outerplanar Graphs.

Franka Bause, Fabian Jogl, Patrick Indri, Tamara Drucks, David Penz, Nils Morten Kriege, Thomas Gärtner, Pascal Welke, Maximilian Thiessen

Trans. Mach. Learn. Res., 2025

A Fine-grained Characterization of PAC Learnability.

Marco Bressan, Nataly Brukhim, Nicolò Cesa-Bianchi, Emmanuel Esposito, Yishay Mansour, Shay Moran, Maximilian Thiessen

Proceedings of the Thirty Eighth Annual Conference on Learning Theory, 2025

Of Dice and Games: A Theory of Generalized Boosting.

Marco Bressan, Nataly Brukhim, Nicolò Cesa-Bianchi, Emmanuel Esposito, Yishay Mansour, Shay Moran, Maximilian Thiessen

Proceedings of the Thirty Eighth Annual Conference on Learning Theory, 2025

Self-Directed Node Classification on Graphs.

Georgy Sokolov, Maximilian Thiessen, Margarita Akhmejanova, Fabio Vitale, Francesco Orabona

Proceedings of the International Conference on Algorithmic Learning Theory, 2025

2024

Self-Directed Learning of Convex Labelings on Graphs.

Georgy Sokolov, Maximilian Thiessen, Margarita Akhmejanova, Fabio Vitale, Francesco Orabona

CoRR, 2024

Bandits with Abstention under Expert Advice.

Stephen Pasteris, Alberto Rumi, Maximilian Thiessen, Shota Saito, Atsushi Miyauchi, Fabio Vitale, Mark Herbster

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Efficient Algorithms for Learning Monophonic Halfspaces in Graphs.

Marco Bressan, Emmanuel Esposito, Maximilian Thiessen

Proceedings of the Thirty Seventh Annual Conference on Learning Theory, June 30, 2024

A Theory of Interpretable Approximations.

Marco Bressan, Nicolò Cesa-Bianchi, Emmanuel Esposito, Yishay Mansour, Shay Moran, Maximilian Thiessen

Proceedings of the Thirty Seventh Annual Conference on Learning Theory, June 30, 2024

2023

Expressivity-Preserving GNN Simulation.

Fabian Jogl, Maximilian Thiessen, Thomas Gärtner

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Expectation-Complete Graph Representations with Homomorphisms.

Pascal Welke, Maximilian Thiessen, Fabian Jogl, Thomas Gärtner

Proceedings of the International Conference on Machine Learning, 2023

2022

Generalized Laplacian Positional Encoding for Graph Representation Learning.

Sohir Maskey, Ali Parviz, Maximilian Thiessen, Hannes Stärk, Ylli Sadikaj, Haggai Maron

CoRR, 2022

Online Learning of Convex Sets on Graphs.

Maximilian Thiessen, Thomas Gärtner

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2022

Active Learning of Classifiers with Label and Seed Queries.

Marco Bressan, Nicolò Cesa-Bianchi, Silvio Lattanzi, Andrea Paudice, Maximilian Thiessen

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Active Learning of Convex Halfspaces on Graphs.

Maximilian Thiessen, Thomas Gärtner

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

Improving a Branch-and-Bound Approach for the Degree-Constrained Minimum Spanning Tree Problem with LKH.

Maximilian Thiessen, Luis Quesada, Kenneth N. Brown

Proceedings of the Integration of Constraint Programming, Artificial Intelligence, and Operations Research, 2020