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02/28/2023
Collaborative Mean Estimation over Intermittently Connected Networks with Peer-To-Peer Privacy
This work considers the problem of Distributed Mean Estimation (DME) ove...
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12/05/2022
Resilient Distributed Optimization for Multi-Agent Cyberphysical Systems
Enhancing resilience in distributed networks in the face of malicious ag...
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05/23/2022
Semi-Decentralized Federated Learning with Collaborative Relaying
We present a semi-decentralized federated learning algorithm wherein cli...
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05/09/2022
Composite IG/FTR Channel Performance in Wireless Communication Systems
We present a composite wireless fading model encompassing multipath fadi...
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02/24/2022
Robust Federated Learning with Connectivity Failures: A Semi-Decentralized Framework with Collaborative Relaying
Intermittent client connectivity is one of the major challenges in centr...
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02/23/2022
Minimax Optimal Quantization of Linear Models: Information-Theoretic Limits and Efficient Algorithms
We consider the problem of quantizing a linear model learned from measur...
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10/03/2021
Cloud-Cluster Architecture for Detection in Intermittently Connected Sensor Networks
We consider a centralized detection problem where sensors experience noi...
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08/06/2021
Alternative Formulations for the Fluctuating Two-Ray Fading Model
We present two alternative formulations for the distribution of the fluc...
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03/13/2021
Distributed Learning and Democratic Embeddings: Polynomial-Time Source Coding Schemes Can Achieve Minimax Lower Bounds for Distributed Gradient Descent under Communication Cons
In this work, we consider the distributed optimization setting where inf...
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01/12/2021
Model-Based Machine Learning for Communications
We present an introduction to model-based machine learning for communica...
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10/30/2020
Interference Reduction in Virtual Cell Optimization
Virtual cell optimization clusters cells into neighborhoods and performs...
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06/05/2020
Inference from Stationary Time Sequences via Learned Factor Graphs
The design of methods for inference from time sequences has traditionall...
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02/14/2020
Data-Driven Symbol Detection via Model-Based Machine Learning
The design of symbol detectors in digital communication systems has trad...
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01/31/2020
Data-Driven Factor Graphs for Deep Symbol Detection
Many important schemes in signal processing and communications, ranging ...
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11/22/2019
Compressed Sensing Channel Estimation for OFDM with non-Gaussian Multipath Gains
This paper analyzes the impact of non-Gaussian multipath component (MPC)...
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11/22/2019
Capacity scaling in a Non-coherent Wideband Massive SIMO Block Fading Channel
The scaling of coherent and non-coherent channel capacity is studied in ...
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11/06/2019
Virtual Cell Clustering with Optimal Resource Allocation to Maximize Capacity
This work proposes a new resource allocation optimization and network ma...
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07/25/2019
Deep Neural Network Symbol Detection for Millimeter Wave Communications
This paper proposes to use a deep neural network (DNN)-based symbol dete...
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05/26/2019
ViterbiNet: A Deep Learning Based Viterbi Algorithm for Symbol Detection
Symbol detection plays an important role in the implementation of digita...
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05/06/2019
Virtual Cell Clustering with Optimal Resource Allocation to Maximize Cellular System Capacity
This work presents a new network optimization framework for cellular net...
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05/06/2019
Optimal Resource Allocation for Cellular Networks with Virtual Cell Joint Decoding
This work presents a new resource allocation optimization framework for ...
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01/20/2019
"Fog" Optimization via Virtual Cells in Cellular Network Resource Allocation
This work proposes a new resource allocation optimization framework for ...
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12/18/2018
Sparse mmWave OFDM Channel Estimation Using Compressed Sensing in OFDM Systems
This paper proposes and analyzes a mmWave sparse channel estimation tech...
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08/01/2018
Orthogonal Time Frequency Space Modulation
This paper introduces a new two-dimensional modulation technique called ...
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02/03/2018
Blind Joint MIMO Channel Estimation and Decoding
We propose a method for MIMO decoding when channel state information (CS...
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01/20/2018
Analog-to-Digital Compression: A New Paradigm for Converting Signals to Bits
Processing, storing and communicating information that originates as an ...
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04/06/2015