2 papers
cs.CL2020
Regularizing Recurrent Neural Networks via Sequence Mixup
Armin Karamzade, Amir Najafi, Seyed Abolfazl Motahari
In this paper, we extend a class of celebrated regularization techniques originally proposed for feed-forward neural networks, namely Input Mixup (Zhang et al., 2017) and Manifold…
cs.LG2018
Structure Learning of Sparse GGMs over Multiple Access Networks
Mostafa Tavassolipour, Armin Karamzade, Reza Mirzaeifard +2
A central machine is interested in estimating the underlying structure of a sparse Gaussian Graphical Model (GGM) from datasets distributed across multiple local machines. The loca…