6 papers · 1 filter
On characterizing optimal learning trajectories in a class of learning problems
Getachew K Befekadu
In this brief paper, we provide a mathematical framework that exploits the relationship between the maximum principle and dynamic programming for characterizing optimal learning tr…
On improving generalization in a class of learning problems with the method of small parameters for weakly-controlled optimal gradient systems
Getachew K. Befekadu
In this paper, we provide a mathematical framework for improving generalization in a class of learning problems which is related to point estimations for modeling of high-dimension…
Further extensions on the successive approximation method for hierarchical optimal control problems and its application to learning
Getachew K. Befekadu
In this paper, further extensions of the result of the paper "A successive approximation method in functional spaces for hierarchical optimal control problems and its application t…
A successive approximation method in functional spaces for hierarchical optimal control problems and its application to learning
Getachew K. Befekadu
We consider a class of learning problem of point estimation for modeling high-dimensional nonlinear functions, whose learning dynamics is guided by model training dataset, while th…
A new perspective on the learning dynamics for a class of learning problems via averaged gradient systems coupled with diffusion-transmutation processes
Getachew K. Befekadu
In the first part of this paper, we consider a family of continuous-time dynamical systems coupled with diffusion-transmutation processes. Under certain conditions, such randomly p…
Embedding generalization within the learning dynamics: An approach based-on sample path large deviation theory
Getachew K. Befekadu
We consider a typical learning problem of point estimations for modeling of nonlinear functions or dynamical systems in which generalization, i.e., verifying a given learned model,…