5 papers
Time Series Classification through Diffeomorphic Time Warping (DiffTW)
Vicky Geneva Haney, Kamel Lahouel, Victor Rielly +1
Time series classification involves learning a mapping from a continuous, temporally ordered sequence of real-valued observations to discrete response variables, like class labels.…
ROCK: A variational formulation for occupation kernel methods in Reproducing Kernel Hilbert Spaces
Victor Rielly, Kamel Lahouel, Chau Nguyen +3
We present a Representer Theorem result for a large class of weak formulation problems. We provide examples of applications of our formulation both in traditional machine learning…
MOCK: an Algorithm for Learning Nonparametric Differential Equations via Multivariate Occupation Kernel Functions
Victor Rielly, Kamel Lahouel, Ethan Lew +4
Learning a nonparametric system of ordinary differential equations from trajectories in a -dimensional state space requires learning functions of variables. Explicit for…
Learning nonparametric ordinary differential equations from noisy data
Kamel Lahouel, Michael Wells, Victor Rielly +3
Learning nonparametric systems of Ordinary Differential Equations (ODEs) dot x = f(t,x) from noisy data is an emerging machine learning topic. We use the well-developed theory of R…
Classification of Minimal Separating Sets in Low Genus Surfaces
J. J. P. Veerman, William J. Maxwell, Victor Rielly +1
Consider a surface and let . If is not connected, then we say \emph{separates} , and we refer to as a \emph{separating set} of . If …