Search Results for author: Krishna R. Narayanan

Found 5 papers, 2 papers with code

PolarAir: A Compressed Sensing Scheme for Over-the-Air Federated Learning

no code implementations24 Jan 2023 Michail Gkagkos, Krishna R. Narayanan, Jean-Francois Chamberland, Costas N. Georghiades

The goal is to create a low complexity, linear compression strategy, called PolarAir, that reduces the size of the gradient at the user side to lower the number of channel uses needed to transmit it.

Federated Learning

Semi-Implicit Graph Variational Auto-Encoders

1 code implementation NeurIPS 2019 Arman Hasanzadeh, Ehsan Hajiramezanali, Nick Duffield, Krishna R. Narayanan, Mingyuan Zhou, Xiaoning Qian

Compared to VGAE, the derived graph latent representations by SIG-VAE are more interpretable, due to more expressive generative model and more faithful inference enabled by the flexible semi-implicit construction.

Variational Inference

Spatially-Coupled Neural Network Architectures

no code implementations3 Jul 2019 Arman Hasanzadeh, Nagaraj T. Janakiraman, Vamsi K. Amalladinne, Krishna R. Narayanan

In this work, we leverage advances in sparse coding techniques to reduce the number of trainable parameters in a fully connected neural network.

Feature Importance

A Graph Signal Processing Approach For Real-Time Traffic Prediction In Transportation Networks

no code implementations19 Nov 2017 Arman Hasanzadeh, Xi Liu, Nick Duffield, Krishna R. Narayanan, Byron Chigoy

Building a prediction model for transportation networks is challenging because spatio-temporal dependencies of traffic data in different roads are complex and the graph constructed from road networks is very large.

Management Time Series Analysis +1

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