News
New paper “Finite-bit Quantization For Distributed Algorithms With Linear Convergence” submitted to IEEE Transactions on Information Theory
A draft of the manuscript is available at https://arxiv.org/pdf/2107.11304.pdf This paper studies distributed algorithms for (strongly convex) composite optimization problems over mesh networks, subject to quantized communications. Instead of focusing on a specific algorithmic design, we propose a black-box model casting distributed algorithms in the form of fixed-point iterates, converging at linear rate. The algorithmic…
Three papers accepted at IEEE GLOBECOM 2021
Three papers from our research group have been accepted and will be presented at IEEE GLOBECOM in Madrid in December 2021! Adaptive Beam Alignment in Mm-Wave Networks: A Deep Variational Autoencoder Architecture, Muddassar Hussain, Nicolò Michelusi Federated Learning Beyond the Star: Local D2D Model Consensus with Global Cluster Sampling, Frank Po-Chen Lin, Seyyedali Hosseinalipour, Sheikh…
Chang-Shen successfully defended his thesis!
Ph.D. candidate Chang-Shen successfully defended his Ph.D. thesis “Distributed Network Processing and Optimization under Communication Constraints.” Congratulations Chang-Shen!
ASU article on the recently awarded NSF CAREER
Muddassar Hussain successfully defended his thesis!
Ph.D. candidate Muddassar Hussain successfully defended his Ph.D. thesis “Beam-Alignment in Millimeter-wave networks: a multiscale approach.” Muddassar will soon join Qualcomm in San Diego. Congratulations Muddassar and best of luck with your new adventure at Qualcomm!
NSF CAREER award received in March 2021
I am honored to receive the NSF CAREER award for the project “Adaptive Communications and Trajectory Design for UAV-assisted Wireless Networks: a Multi-Scale Decision Framework” from the National Science Foundation. Thank you, NSF The demand for wireless broadband is growing in the United States and across the world. Unmanned aerial vehicles (UAVs) are envisioned as…
New paper accepted at IEEE ICC 2021
Our new paper “Learning-based Cognitive Radio Access via Randomized Point-Based Approximate POMDPs,” coauthored with my student Bharath Keshavamurthy, has been accepted at IEEE ICC 2021 and will be presented this June! In this paper, a novel spectrum sensing and access strategy based on approximate Partially Observable Markov Decision Processes (POMDPs) is proposed, wherein a cognitive…
New paper accepted in the IEEE Journal of Selected Topics in Signal Processing
Our new paper “Fast Position-Aided MIMO Beam Training via Noisy Tensor Completion,” coauthored with my student Tzu-Hsuan Chou and colleagues David J. Love and James V. Krogmeier from Purdue University has been accepted in the IEEE Journal of Selected Topics in Signal Processing, Special Issue on Tensor Decomposition for Signal Processing and Machine Learning. In this…