David Reeb

According to our database, David Reeb authored at least 14 papers between 2015 and 2024.

Collaborative distances:

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

2024

Tighter Confidence Bounds for Sequential Kernel Regression.

Hamish Flynn, David Reeb

CoRR, 2024

2023

PAC-Bayes Bounds for Bandit Problems: A Survey and Experimental Comparison.

Hamish Flynn, David Reeb, Melih Kandemir, Jan Peters

IEEE Trans. Pattern Anal. Mach. Intell., December, 2023

A refinement of Reznick's Positivstellensatz with applications to quantum information theory.

Alexander Müller-Hermes, Ion Nechita, David Reeb

Quantum, May, 2023

Validation of composite systems by discrepancy propagation.

David Reeb, Kanil Patel, Karim Said Barsim, Martin Schiegg, Sebastian Gerwinn

Proceedings of the Uncertainty in Artificial Intelligence, 2023

Improved Algorithms for Stochastic Linear Bandits Using Tail Bounds for Martingale Mixtures.

Hamish Flynn, David Reeb, Melih Kandemir, Jan R. Peters

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

2022

PAC-Bayesian lifelong learning for multi-armed bandits.

Hamish Flynn, David Reeb, Melih Kandemir, Jan Peters

Data Min. Knowl. Discov., 2022

Utilizing Expert Features for Contrastive Learning of Time-Series Representations.

Manuel T. Nonnenmacher, Lukas Oldenburg, Ingo Steinwart, David Reeb

Proceedings of the International Conference on Machine Learning, 2022

SOSP: Efficiently Capturing Global Correlations by Second-Order Structured Pruning.

Manuel Nonnenmacher, Thomas Pfeil, Ingo Steinwart, David Reeb

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Which Minimizer Does My Neural Network Converge To?

Manuel Nonnenmacher, David Reeb, Ingo Steinwart

Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2021

2020

Beyond the Mean-Field: Structured Deep Gaussian Processes Improve the Predictive Uncertainties.

Jakob Lindinger, David Reeb, Christoph Lippert, Barbara Rakitsch

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2018

Bounds on Information Combining With Quantum Side Information.

Christoph Hirche, David Reeb

IEEE Trans. Inf. Theory, 2018

Learning Gaussian Processes by Minimizing PAC-Bayesian Generalization Bounds.

David Reeb, Andreas Doerr, Sebastian Gerwinn, Barbara Rakitsch

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2015

Tight Bound on Relative Entropy by Entropy Difference.

David Reeb, Michael M. Wolf

IEEE Trans. Inf. Theory, 2015

Quantum Subdivision Capacities and Continuous-Time Quantum Coding.

Alexander Müller-Hermes, David Reeb, Michael M. Wolf

IEEE Trans. Inf. Theory, 2015