We consider the nonlinear inverse problem of learning a transition opera...
Dynamical systems across many disciplines are modeled as interacting
par...
We investigate the unsupervised learning of non-invertible observation
f...
Building accurate and predictive models of the underlying mechanisms of
...
We introduce a nonlinear stochastic model reduction technique for
high-d...
Interacting agent and particle systems are extensively used to model com...
We consider the regression problem of estimating functions on ℝ^D
but su...
Many cardiac diseases are associated with structural remodeling of the
m...
Modeling the complex interactions of systems of particles or agents is a...
We consider stochastic systems of interacting particles or agents, with
...
The single-index model is a statistical model for intrinsic regression w...
Identifiability is of fundamental importance in the statistical learning...
Particle- and agent-based systems are a ubiquitous modeling tool in many...
Systems of interacting particles or agents have wide applications in man...
This article proposes an active learning method for high dimensional dat...
An unsupervised learning algorithm to cluster hyperspectral image (HSI) ...
Inferring the laws of interaction between particles and agents in comple...
This paper proposes and analyzes a novel clustering algorithm that combi...
We consider the problem of clustering with the longest leg path distance...
Classification of individual samples into one or more categories is crit...
We consider the problem of efficiently approximating and encoding
high-d...
Determining whether certain properties are related to other properties i...
We briefly review recent progress in techniques for modeling and analyzi...
Random forests (RF) is a popular general purpose classifier that has bee...
Many problems in sequential decision making and stochastic control often...
Data sets are often modeled as point clouds in R^D, for D large. It is
o...