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Papers matching “high-dimensional problems” 36

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Deep Model-Based Reinforcement Learning for High-Dimensional Problems, a Survey
2020 arXiv (Cornell University) preprint Computer Science Reinforcement Learning in Robotics Open access

Aske Plaat, Walter A. Kosters, Mike Preuß

6

citations
Iterative thresholding low-rank time integration for high-dimensional problems
2026 arXiv (Cornell University) preprint Mathematics Numerical methods for differential equations Open access

Markus Bachmayr, Tianyu Jin, Polina Sachsenmaier, Federico Vismara

0

citations
Dynamical low-rank tensor approximations to high-dimensional parabolic problems: existence and convergence of spatial discretizations
2023 arXiv (Cornell University) preprint Mathematics Tensor decomposition and applications Open access

Markus Bachmayr, Henrik Eisenmann, André Uschmajew

1

citations
Projection inference for high-dimensional covariance matrices with structured shrinkage targets
2022 arXiv (Cornell University) preprint Mathematics Statistical Methods and Inference Open access

Fabian Mies, Ansgar Steland

0

citations
Non-Asymptotic Uncertainty Quantification in High-Dimensional Learning
2024 arXiv (Cornell University) preprint Mathematics Statistical Methods and Inference Open access

Frederik Hoppe, Claudio Mayrink Verdun, Hannah Laus, Felix Krahmer, Holger Rauhut

0

citations
Comparison of High-Dimensional Bayesian Optimization Algorithms on BBOB
2023 arXiv (Cornell University) preprint Decision Sciences Advanced Bandit Algorithms Research Open access

Maria Laura Santoni, Elena Raponi, Renato De Leone, Carola Doerr

2

citations
Detecting Changes in the Second Moment Structure of High-Dimensional Sensor-Type Data in a $K$-Sample Setting
2020 arXiv (Cornell University) preprint Decision Sciences Advanced Statistical Process Monitoring Open access

Nils Mause, Ansgar Steland

0

citations
High Dimensional Bayesian Optimization with Kernel Principal Component Analysis
2022 arXiv (Cornell University) preprint Decision Sciences Advanced Bandit Algorithms Research Open access

Kirill Antonov, Elena Raponi, Hao Wang, Carola Doerr

2

citations
A comparison study of supervised learning techniques for the approximation of high dimensional functions and feedback control
2024 arXiv (Cornell University) preprint Computer Science Neural Networks and Applications Open access

Mathias Oster, Luca Saluzzi, Tizian Wenzel

1

citations
Analysis of modular CMA-ES on strict box-constrained problems in the SBOX-COST benchmarking suite
2023 arXiv (Cornell University) preprint Computer Science Metaheuristic Optimization Algorithms Research Open access

Diederick Vermetten, Manuel López‐Ibáñez, Olaf Mersmann, Richard Allmendinger, Anna V. Kononova

0

citations
Deep Learning of Causal Structures in High Dimensions
2022 arXiv (Cornell University) preprint Computer Science Bayesian Modeling and Causal Inference Open access

Kai Lagemann, Christian Lagemann, Bernd Taschler, Sach Mukherjee

0

citations
High-Accuracy Model-Based Reinforcement Learning, a Survey
2021 arXiv (Cornell University) preprint Computer Science Reinforcement Learning in Robotics Open access

Aske Plaat, Walter A. Kosters, Mike Preuß

5

citations
Efficient localised model reduction for multiscale PDEs via Grassmannian interpolation
2026 arXiv (Cornell University) preprint Physics and Astronomy Model Reduction and Neural Networks Open access

Christian Alber, Markus Bachmayr, Robert Scheichl, Huqing Yang

0

citations
Local Preferential Bayesian Optimization
2026 arXiv (Cornell University) preprint Decision Sciences Advanced Bandit Algorithms Research Open access

Johanna Menn, Miriam Kober, Paul Brunzema, David Stenger, Sebastian Trimpe

0

citations
Phantom-Conditioned Nested Sampling
2026 arXiv (Cornell University) preprint Mathematics Markov Chains and Monte Carlo Methods Open access

Joshua G. Albert

0

citations
Almanac: HMC sampling with bounded velocity
2026 arXiv (Cornell University) preprint Mathematics Markov Chains and Monte Carlo Methods Open access

Javier Silva Lafaurie, L Whiteway, Elena Sellentin, Kutay Nazli, Andrew H. Jaffe, Alan Heavens, +1 more

0

citations
On Safety in Safe Bayesian Optimization
2024 arXiv (Cornell University) preprint Decision Sciences Advanced Bandit Algorithms Research Open access

Christian Fiedler, Johanna Menn, Lukas Kreisköther, Sebastian Trimpe

3

citations
Permutation-based multiple testing when fitting many generalized linear models
2024 arXiv (Cornell University) preprint Mathematics Statistical Methods and Inference Open access

Riccardo De Santis, Jelle J. Goeman, Samuel Davenport, Jesse Hemerik, Livio Finos

0

citations
With or Without Replacement? Improving Confidence in Fourier Imaging
2024 arXiv (Cornell University) preprint Engineering Sparse and Compressive Sensing Techniques Open access

Frederik Hoppe, Claudio Mayrink Verdun, Felix Krahmer, Marion Irene Menzel, Holger Rauhut

0

citations
Safety in safe Bayesian optimization and its ramifications for control
2025 arXiv (Cornell University) preprint Decision Sciences Advanced Bandit Algorithms Research Open access

Christian Fiedler, Johanna Menn, Sebastian Trimpe

0

citations
ManQala: Game-Inspired Strategies for Quantum State Engineering
2023 arXiv (Cornell University) preprint Computer Science Quantum Computing Algorithms and Architecture Open access

Onur Danaci, Wenlei Zhang, William Djakam, Michaela Amoo, Ryan T. Glasser, Brian T. Kirby, +2 more

0

citations
Feasibility-Driven Trust Region Bayesian Optimization
2025 arXiv (Cornell University) preprint Decision Sciences Advanced Bandit Algorithms Research Open access

Paolo Ascia, Elena Raponi, Thomas Bäck, Fabian M. E. Duddeck

0

citations
Online Detection of Changes in Moment-Based Projections: When to Retrain Deep Learners or Update Portfolios?
2023 arXiv (Cornell University) preprint Mathematics Statistical Methods and Inference Open access

Ansgar Steland

0

citations
A Greedy Sensor Selection Algorithm for Hyperparameterized Linear Bayesian Inverse Problems
2023 arXiv (Cornell University) preprint Decision Sciences Optimal Experimental Design Methods Open access

Nicole Aretz, Peng Chen, Denise Degen, Karen Veroy

0

citations
Ensemble Kalman Inversion as an Inertial Interacting Particle System
2026 arXiv (Cornell University) preprint Mathematics Markov Chains and Monte Carlo Methods Open access

Michael Herty, Pierpaolo Porretta, Giuseppe Visconti

0

citations