9 citations · 9 across the 1 of their papers we have counts for
5 papers
On Convergence and Generalization of Dropout Training
Poorya Mianjy, Raman Arora
We study dropout in two-layer neural networks with rectified linear unit (ReLU) activations. Under mild overparametrization and assuming that the limiting kernel can separate the d…
Dropout: Explicit Forms and Capacity Control
Raman Arora, Peter Bartlett, Poorya Mianjy +1
We investigate the capacity control provided by dropout in various machine learning problems. First, we study dropout for matrix completion, where it induces a data-dependent regul…
On Dropout and Nuclear Norm Regularization
Poorya Mianjy, Raman Arora
We give a formal and complete characterization of the explicit regularizer induced by dropout in deep linear networks with squared loss. We show that (a) the explicit regularizer i…
Streaming Kernel PCA with Random Features
Enayat Ullah, Poorya Mianjy, Teodor V. Marinov +1
We study the statistical and computational aspects of kernel principal component analysis using random Fourier features and show that under mild assumptions, f…
On the Implicit Bias of Dropout
Poorya Mianjy, Raman Arora, Rene Vidal
Algorithmic approaches endow deep learning systems with implicit bias that helps them generalize even in over-parametrized settings. In this paper, we focus on understanding such a…