Optimal Rates for Regularized Conditional Mean Embedding Learning

2 August 2022

Papers citing "Optimal Rates for Regularized Conditional Mean Embedding Learning"

34 / 34 papers shown

Title
Koopman-Equivariant Gaussian Processes Petar Bevanda Max Beier Armin Lederer A. Capone Stefan Sosnowski Sandra Hirche AI4TS 61 1 0 10 Feb 2025
Kernel-Based Optimal Control: An Infinitesimal Generator Approach Petar Bevanda Nicolas Hosichen Tobias Wittmann Jan Brüdigam Sandra Hirche Boris Houska 65 0 0 02 Dec 2024
An Overview of Causal Inference using Kernel Embeddings Dino Sejdinovic CML BDL 27 2 0 30 Oct 2024
Laplace Transform Based Low-Complexity Learning of Continuous Markov Semigroups Vladimir Kostic Karim Lounici Helene Halconruy Timothée Devergne P. Novelli Massimiliano Pontil 21 0 0 18 Oct 2024
Data-Driven Optimal Feedback Laws via Kernel Mean Embeddings Petar Bevanda Nicolas Hoischen Stefan Sosnowski Sandra Hirche Boris Houska 18 2 0 23 Jul 2024
Spectral Representation for Causal Estimation with Hidden Confounders Tongzheng Ren Haotian Sun Antoine Moulin Arthur Gretton Bo Dai CML 24 1 0 15 Jul 2024
Operator World Models for Reinforcement Learning P. Novelli Marco Prattico Massimiliano Pontil C. Ciliberto OffRL 34 0 0 28 Jun 2024
On the Consistency of Kernel Methods with Dependent Observations P. Massiani Sebastian Trimpe Friedrich Solowjow 13 0 0 10 Jun 2024
Optimal Rates for Vector-Valued Spectral Regularization Learning Algorithms D. Meunier Zikai Shen Mattes Mollenhauer Arthur Gretton Zhu Li 29 4 0 23 May 2024
Learning the Infinitesimal Generator of Stochastic Diffusion Processes Vladimir Kostic Karim Lounici Helene Halconruy Timothée Devergne Massimiliano Pontil DiffM 19 4 0 21 May 2024
Data-Driven Distributionally Robust Safety Verification Using Barrier Certificates and Conditional Mean Embeddings Oliver Schon Zhengang Zhong Sadegh Soudjani 19 7 0 15 Mar 2024
Practical Kernel Tests of Conditional Independence Roman Pogodin Antonin Schrab Yazhe Li Danica J. Sutherland A. Gretton 35 4 0 20 Feb 2024
Spectrally Transformed Kernel Regression Runtian Zhai Rattana Pukdee Roger Jin Maria-Florina Balcan Pradeep Ravikumar BDL 13 2 0 01 Feb 2024
Consistent Long-Term Forecasting of Ergodic Dynamical Systems Prune Inzerilli Vladimir Kostic Karim Lounici P. Novelli Massimiliano Pontil 8 4 0 20 Dec 2023
Towards Optimal Sobolev Norm Rates for the Vector-Valued Regularized Least-Squares Algorithm Zhu Li D. Meunier Mattes Mollenhauer Arthur Gretton 21 5 0 12 Dec 2023
Kernel Single Proxy Control for Deterministic Confounding Liyuan Xu A. Gretton CML 19 2 0 08 Aug 2023
Learning invariant representations of time-homogeneous stochastic dynamical systems Vladimir Kostic P. Novelli Riccardo Grazzi Karim Lounici Massimiliano Pontil 14 7 0 19 Jul 2023
Conditional expectation using compactification operators Suddhasattwa Das 15 3 0 18 Jun 2023
Estimating Koopman operators with sketching to provably learn large scale dynamical systems Giacomo Meanti Antoine Chatalic Vladimir Kostic P. Novelli Massimiliano Pontil Lorenzo Rosasco 6 9 0 07 Jun 2023
On the Optimality of Misspecified Kernel Ridge Regression Haobo Zhang Yicheng Li Weihao Lu Qian Lin 34 12 0 12 May 2023
Propagating Kernel Ambiguity Sets in Nonlinear Data-driven Dynamics Models Jia-Jie Zhu 8 0 0 27 Apr 2023
An Efficient Doubly-Robust Test for the Kernel Treatment Effect Diego Martinez-Taboada Aaditya Ramdas Edward H. Kennedy OOD 18 5 0 26 Apr 2023
On the Optimality of Misspecified Spectral Algorithms Hao Zhang Yicheng Li Qian Lin 8 14 0 27 Mar 2023
Sharp Spectral Rates for Koopman Operator Learning Vladimir Kostic Karim Lounici P. Novelli Massimiliano Pontil 22 20 0 03 Feb 2023
Returning The Favour: When Regression Benefits From Probabilistic Causal Knowledge S. Bouabid Jake Fawkes Dino Sejdinovic CML 31 0 0 26 Jan 2023
Physics-Informed Kernel Embeddings: Integrating Prior System Knowledge with Data-Driven Control Adam J. Thorpe Cyrus Neary Franck Djeumou Meeko Oishi Ufuk Topcu 12 7 0 09 Jan 2023
Efficient Conditionally Invariant Representation Learning Roman Pogodin Namrata Deka Yazhe Li Danica J. Sutherland Victor Veitch A. Gretton BDL OOD CML 17 16 0 16 Dec 2022
Learning linear operators: Infinite-dimensional regression as a well-behaved non-compact inverse problem Mattes Mollenhauer Nicole Mücke T. Sullivan 19 24 0 16 Nov 2022
Minimax Optimal Kernel Operator Learning via Multilevel Training Jikai Jin Yiping Lu Jose H. Blanchet Lexing Ying 16 11 0 28 Sep 2022
Sequential Kernel Embedding for Mediated and Time-Varying Dose Response Curves Rahul Singh Liyuan Xu A. Gretton 24 3 0 06 Nov 2021
Nonparametric approximation of conditional expectation operators Mattes Mollenhauer P. Koltai 21 17 0 23 Dec 2020
Kernel Methods for Causal Functions: Dose, Heterogeneous, and Incremental Response Curves Rahul Singh Liyuan Xu A. Gretton OffRL 40 26 0 10 Oct 2020
Universal Robust Regression via Maximum Mean Discrepancy Pierre Alquier Mathieu Gerber 25 15 0 01 Jun 2020
Kernel Autocovariance Operators of Stationary Processes: Estimation and Convergence Mattes Mollenhauer Stefan Klus Christof Schütte P. Koltai 17 8 0 02 Apr 2020