David Reeb
7 papers · 2018–2025 · 5 venues · across top CS/AI venues
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Achievements
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Conference Polyglot · Silver
🏃
Academic Marathon · Sprint
🌉
Interdisciplinary Bridge · Bronze
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Taxonomy Completionist
(19)
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Trend Setter
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Research topics
Machine Learning
(7)
Optimization & Theory
(4)
Bayesian & Probabilistic · Machine Learning
(3)
Learning Types
(3)
Artificial Intelligence
(2)
Mathematics & Optimization
(2)
Core Methods
(2)
Optimization
(2)
Deep Learning
(1)
Bayesian & Probabilistic · Artificial Intelligence
(1)
Core AI
(1)
Techniques
(1)
Keywords
gaussian process
(2)
unsupervised learning
(1)
neural network pruning
(1)
representation learning
(1)
contrastive learning
(1)
probabilistic modeling
(1)
variational inference
(1)
bayesian inference
(1)
uncertainty quantification
(1)
supervised learning
(1)
marginal likelihood
(1)
regret minimization
(1)
convex relaxation
(1)
sparse approximation
(1)
kernel regression
(1)
maximum mean discrepancy
(1)
convex programming
(1)
martingale tail inequality
(1)
second-order optimization
(1)
generalization bound
(1)
Papers
Tighter Confidence Bounds for Sequential Kernel Regression
AISTATS 2025
Improved Algorithms for Stochastic Linear Bandits Using Tail Bounds for Martingale Mixtures
NeurIPS 2023
Validation of composite systems by discrepancy propagation
UAI 2023
SOSP: Efficiently Capturing Global Correlations by Second-Order Structured Pruning
ICLR 2022
Utilizing Expert Features for Contrastive Learning of Time-Series Representations
ICML 2022
Beyond the Mean-Field: Structured Deep Gaussian Processes Improve the Predictive Uncertainties
NeurIPS 2020
Learning Gaussian Processes by Minimizing PAC-Bayesian Generalization Bounds
NeurIPS 2018