8 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…
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…
Coarse-to-fine Multiple Testing Strategies
Kamel Lahouel, Donald Geman, Laurent Younes
We analyze control of the familywise error rate (FWER) in a multiple testing scenario with a great many null hypotheses about the distribution of a high-dimensional random variable…
Non-Adaptive Policies for 20 Questions Target Localization
Ehsan Variani, Kamel Lahouel, Avner Bar-Hen +1
The problem of target localization with noise is addressed. The target is a sample from a continuous random variable with known distribution and the goal is to locate it with minim…