3 citations · 3 across the 5 of their papers we have counts for
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.…
The Stochastic Occupation Kernel (SOCK) Method for Learning Stochastic Differential Equations
Michael L. Wells, Kamel Lahouel, Bruno Jedynak
We present a novel kernel-based method for learning multivariate stochastic differential equations (SDEs). The method follows a two-step procedure: we first estimate the drift term…
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…
The Stochastic Occupation Kernel Method for System Identification
Michael Wells, Kamel Lahouel, Bruno Jedynak
The method of occupation kernels has been used to learn ordinary differential equations from data in a non-parametric way. We propose a two-step method for learning the drift and d…
A Finite-Horizon Approach to Active Level Set Estimation
Phillip Kearns, Bruno Jedynak, John Lipor
We consider the problem of active learning in the context of spatial sampling for level set estimation (LSE), where the goal is to localize all regions where a function of interest…