6 citations · 13 across the 6 of their papers we have counts for
7 papers
Structure Learning in Graphical Models from Indirect Observations
Hang Zhang, Afshin Abdi, Faramarz Fekri
This paper considers learning of the graphical structure of a -dimensional random vector using both parametric and non-parametric methods. Unlike the previous works…
A General Compressive Sensing Construct using Density Evolution
Hang Zhang, Afshin Abdi, Faramarz Fekri
This paper proposes a general framework to design a sparse sensing matrix $\ensuremath{\mathbf{A}}\in \mathbb{R}^{m\times n}$, in a linear measurement system $\ensuremath{\mathbf{y…
A Machine Learning Framework for Distributed Functional Compression over Wireless Channels in IoT
Yashas Malur Saidutta, Afshin Abdi, Faramarz Fekri
IoT devices generating enormous data and state-of-the-art machine learning techniques together will revolutionize cyber-physical systems. In many diverse fields, from autonomous dr…
Restructuring, Pruning, and Adjustment of Deep Models for Parallel Distributed Inference
Afshin Abdi, Saeed Rashidi, Faramarz Fekri +1
Using multiple nodes and parallel computing algorithms has become a principal tool to improve training and execution times of deep neural networks as well as effective collective i…
Nested Dithered Quantization for Communication Reduction in Distributed Training
Afshin Abdi, Faramarz Fekri
In distributed training, the communication cost due to the transmission of gradients or the parameters of the deep model is a major bottleneck in scaling up the number of processin…
Compressive Sensing with a Multiple Convex Sets Domain
Hang Zhang, Afshin Abdi, Faramarz Fekri
In this paper, we study a general framework for compressive sensing assuming the existence of the prior knowledge that belongs to the union of multiple convex se…