David Reeb

Publication Activity (10 Years)

Years Active: 2013-2024
Publications (10 Years): 23

Top Topics

Gaussian Process

Lifelong Learning

Multi Armed Bandits

Top Venues

IEEE Trans. Inf. Theory

Publications

Hamish Flynn, David Reeb
Tighter Confidence Bounds for Sequential Kernel Regression. CoRR (2024)
Alexander Müller-Hermes, Ion Nechita, David Reeb
A refinement of Reznick's Positivstellensatz with applications to quantum information theory. Quantum 7 (2023)
Hamish Flynn, David Reeb, Melih Kandemir, Jan R. Peters
Improved Algorithms for Stochastic Linear Bandits Using Tail Bounds for Martingale Mixtures. NeurIPS (2023)
Hamish Flynn, David Reeb, Melih Kandemir, Jan Peters
PAC-Bayes Bounds for Bandit Problems: A Survey and Experimental Comparison. IEEE Trans. Pattern Anal. Mach. Intell. 45 (12) (2023)
David Reeb, Kanil Patel, Karim Said Barsim, Martin Schiegg, Sebastian Gerwinn
Validation of composite systems by discrepancy propagation. UAI (2023)
Hamish Flynn, David Reeb, Melih Kandemir, Jan Peters
Improved Algorithms for Stochastic Linear Bandits Using Tail Bounds for Martingale Mixtures. CoRR (2023)
Hamish Flynn, David Reeb, Melih Kandemir, Jan Peters
PAC-Bayesian lifelong learning for multi-armed bandits. Data Min. Knowl. Discov. 36 (2) (2022)
Manuel Nonnenmacher, Thomas Pfeil, Ingo Steinwart, David Reeb
SOSP: Efficiently Capturing Global Correlations by Second-Order Structured Pruning. ICLR (2022)
Hamish Flynn, David Reeb, Melih Kandemir, Jan Peters
PAC-Bayesian Lifelong Learning For Multi-Armed Bandits. CoRR (2022)
Manuel Nonnenmacher, Lukas Oldenburg, Ingo Steinwart, David Reeb
Utilizing Expert Features for Contrastive Learning of Time-Series Representations. CoRR (2022)
David Reeb, Kanil Patel, Karim Barsim, Martin Schiegg, Sebastian Gerwinn
Validation of Composite Systems by Discrepancy Propagation. CoRR (2022)
Hamish Flynn, David Reeb, Melih Kandemir, Jan Peters
PAC-Bayes Bounds for Bandit Problems: A Survey and Experimental Comparison. CoRR (2022)
Manuel T. Nonnenmacher, Lukas Oldenburg, Ingo Steinwart, David Reeb
Utilizing Expert Features for Contrastive Learning of Time-Series Representations. ICML (2022)
Manuel Nonnenmacher, David Reeb, Ingo Steinwart
Which Minimizer Does My Neural Network Converge To? ECML/PKDD (3) (2021)
Manuel Nonnenmacher, Thomas Pfeil, Ingo Steinwart, David Reeb
SOSP: Efficiently Capturing Global Correlations by Second-Order Structured Pruning. CoRR (2021)
Jakob Lindinger, David Reeb, Christoph Lippert, Barbara Rakitsch
Beyond the Mean-Field: Structured Deep Gaussian Processes Improve the Predictive Uncertainties. CoRR (2020)
Jakob Lindinger, David Reeb, Christoph Lippert, Barbara Rakitsch
Beyond the Mean-Field: Structured Deep Gaussian Processes Improve the Predictive Uncertainties. NeurIPS (2020)
Manuel Nonnenmacher, David Reeb, Ingo Steinwart
Which Minimizer Does My Neural Network Converge To? CoRR (2020)
Christoph Hirche, David Reeb
Bounds on Information Combining with Quantum Side Information. ISIT (2018)
David Reeb, Andreas Doerr, Sebastian Gerwinn, Barbara Rakitsch
Learning Gaussian Processes by Minimizing PAC-Bayesian Generalization Bounds. CoRR (2018)
Christoph Hirche, David Reeb
Bounds on Information Combining With Quantum Side Information. IEEE Trans. Inf. Theory 64 (7) (2018)
David Reeb, Andreas Doerr, Sebastian Gerwinn, Barbara Rakitsch
Learning Gaussian Processes by Minimizing PAC-Bayesian Generalization Bounds. NeurIPS (2018)
Christoph Hirche, David Reeb
Bounds on Information Combining With Quantum Side Information. CoRR (2017)
David Reeb, Michael M. Wolf
Tight Bound on Relative Entropy by Entropy Difference. IEEE Trans. Inf. Theory 61 (3) (2015)
Alexander Müller-Hermes, David Reeb, Michael M. Wolf
Quantum Subdivision Capacities and Continuous-Time Quantum Coding. IEEE Trans. Inf. Theory 61 (1) (2015)
David Reeb, Michael M. Wolf
Tight bound on relative entropy by entropy difference CoRR (2013)