154 citations · 861 across the 94 of their papers we have counts for
5 papers · 2 filters
Overparameterized Nonlinear Learning: Gradient Descent Takes the Shortest Path?
Samet Oymak, Mahdi Soltanolkotabi
Many modern learning tasks involve fitting nonlinear models to data which are trained in an overparameterized regime where the parameters of the model exceed the size of the traini…
Stochastic Gradient Descent Learns State Equations with Nonlinear Activations
Samet Oymak
We study discrete time dynamical systems governed by the state equation . Here are weight matrices, is an activation function, and is the inpu…
Non-asymptotic Identification of LTI Systems from a Single Trajectory
Samet Oymak, Necmiye Ozay
We consider the problem of learning a realization for a linear time-invariant (LTI) dynamical system from input/output data. Given a single input/output trajectory, we provide fini…
End-to-end Learning of a Convolutional Neural Network via Deep Tensor Decomposition
Samet Oymak, Mahdi Soltanolkotabi
In this paper we study the problem of learning the weights of a deep convolutional neural network. We consider a network where convolutions are carried out over non-overlapping pat…
Learning Compact Neural Networks with Regularization
Samet Oymak
Proper regularization is critical for speeding up training, improving generalization performance, and learning compact models that are cost efficient. We propose and analyze regula…