From the 1 of 4 linked papers with an AI index.
4 papers
Learning Ergodic Dynamical Systems from a Finite Trajectory
Oleksii Kachaiev, Silvia Villa, Lorenzo Rosasco
We consider the problem of learning from a single finite trajectory of an ergodic stochastic dynamical system. More precisely, we study discrete-time autonomous stochastic systems…
Learning to control switching nonlinear systems with Koopman operator regression
Edoardo Caldarelli, Oleksii Kachaiev, Cesare Molinari +1
The paper proposes using Koopman operator regression in a reproducing kernel Hilbert space to identify and control nonlinear systems with finite action spaces, creating a linear sw…
SKADA-Bench: Benchmarking Unsupervised Domain Adaptation Methods with Realistic Validation On Diverse Modalities
Yanis Lalou, Théo Gnassounou, Antoine Collas +6
Unsupervised Domain Adaptation (DA) consists of adapting a model trained on a labeled source domain to perform well on an unlabeled target domain with some data distribution shift.…
Learning to Embed Distributions via Maximum Kernel Entropy
Oleksii Kachaiev, Stefano Recanatesi
Empirical data can often be considered as samples from a set of probability distributions. Kernel methods have emerged as a natural approach for learning to classify these distribu…