David Reeb - RankMe

27 papers A* 5A 2B 1Journal 18Unranked 1

Year	Rank	Type	Title / Venue / Authors
2025	A	`conf`	Tighter Confidence Bounds for Sequential Kernel Regression. AISTATS Hamish Flynn, David Reeb
2024	J	`jnl`	Tighter Confidence Bounds for Sequential Kernel Regression. CoRR Hamish Flynn, David Reeb
2023	J	`jnl`	A refinement of Reznick's Positivstellensatz with applications to quantum information theory. Quantum Alexander Müller-Hermes, Ion Nechita, David Reeb
2023	A*	`conf`	Improved Algorithms for Stochastic Linear Bandits Using Tail Bounds for Martingale Mixtures. NeurIPS Hamish Flynn, David Reeb, Melih Kandemir, Jan R. Peters
2023	J	`jnl`	Improved Algorithms for Stochastic Linear Bandits Using Tail Bounds for Martingale Mixtures. CoRR Hamish Flynn, David Reeb, Melih Kandemir, Jan Peters
2023	J	`jnl`	PAC-Bayes Bounds for Bandit Problems: A Survey and Experimental Comparison. IEEE Trans. Pattern Anal. Mach. Intell. Hamish Flynn, David Reeb, Melih Kandemir, Jan Peters
2023	A	`conf`	Validation of composite systems by discrepancy propagation. UAI David Reeb, Kanil Patel, Karim Said Barsim, Martin Schiegg, Sebastian Gerwinn
2022	J	`jnl`	PAC-Bayes Bounds for Bandit Problems: A Survey and Experimental Comparison. CoRR Hamish Flynn, David Reeb, Melih Kandemir, Jan Peters
2022	J	`jnl`	PAC-Bayesian Lifelong Learning For Multi-Armed Bandits. CoRR Hamish Flynn, David Reeb, Melih Kandemir, Jan Peters
2022	J	`jnl`	PAC-Bayesian lifelong learning for multi-armed bandits. Data Min. Knowl. Discov. Hamish Flynn, David Reeb, Melih Kandemir, Jan Peters
2022	A*	`conf`	SOSP: Efficiently Capturing Global Correlations by Second-Order Structured Pruning. ICLR Manuel Nonnenmacher, Thomas Pfeil, Ingo Steinwart, David Reeb
2022	A*	`conf`	Utilizing Expert Features for Contrastive Learning of Time-Series Representations. ICML Manuel T. Nonnenmacher, Lukas Oldenburg, Ingo Steinwart, David Reeb
2022	J	`jnl`	Utilizing Expert Features for Contrastive Learning of Time-Series Representations. CoRR Manuel Nonnenmacher, Lukas Oldenburg, Ingo Steinwart, David Reeb
2022	J	`jnl`	Validation of Composite Systems by Discrepancy Propagation. CoRR David Reeb, Kanil Patel, Karim Said Barsim, Martin Schiegg, Sebastian Gerwinn
2021	J	`jnl`	SOSP: Efficiently Capturing Global Correlations by Second-Order Structured Pruning. CoRR Manuel Nonnenmacher, Thomas Pfeil, Ingo Steinwart, David Reeb
2021	—	`conf`	Which Minimizer Does My Neural Network Converge To? ECML/PKDD (3) Manuel Nonnenmacher, David Reeb, Ingo Steinwart
2020	A*	`conf`	Beyond the Mean-Field: Structured Deep Gaussian Processes Improve the Predictive Uncertainties. NeurIPS Jakob Lindinger, David Reeb, Christoph Lippert, Barbara Rakitsch
2020	J	`jnl`	Beyond the Mean-Field: Structured Deep Gaussian Processes Improve the Predictive Uncertainties. CoRR Jakob Lindinger, David Reeb, Christoph Lippert, Barbara Rakitsch
2020	J	`jnl`	Which Minimizer Does My Neural Network Converge To? CoRR Manuel Nonnenmacher, David Reeb, Ingo Steinwart
2018	J	`jnl`	Bounds on Information Combining With Quantum Side Information. IEEE Trans. Inf. Theory Christoph Hirche, David Reeb
2018	B	`conf`	Bounds on Information Combining with Quantum Side Information. ISIT Christoph Hirche, David Reeb
2018	A*	`conf`	Learning Gaussian Processes by Minimizing PAC-Bayesian Generalization Bounds. NeurIPS David Reeb, Andreas Doerr, Sebastian Gerwinn, Barbara Rakitsch
2018	J	`jnl`	Learning Gaussian Processes by Minimizing PAC-Bayesian Generalization Bounds. CoRR David Reeb, Andreas Doerr, Sebastian Gerwinn, Barbara Rakitsch
2017	J	`jnl`	Bounds on Information Combining With Quantum Side Information. CoRR Christoph Hirche, David Reeb
2015	J	`jnl`	Quantum Subdivision Capacities and Continuous-Time Quantum Coding. IEEE Trans. Inf. Theory Alexander Müller-Hermes, David Reeb, Michael M. Wolf
2015	J	`jnl`	Tight Bound on Relative Entropy by Entropy Difference. IEEE Trans. Inf. Theory David Reeb, Michael M. Wolf
2013	J	`jnl`	Tight bound on relative entropy by entropy difference CoRR David Reeb, Michael M. Wolf