434 citations · 1.3k across the 83 of their papers we have counts for
14 papers · 1 filter
One Pixel Image and RF Signal Based Split Learning for mmWave Received Power Prediction
Yusuke Koda, Jihong Park, Mehdi Bennis +3
Focusing on the received power prediction of millimeter-wave (mmWave) radio-frequency (RF) signals, we propose a multimodal split learning (SL) framework that integrates RF receive…
L-FGADMM: Layer-Wise Federated Group ADMM for Communication Efficient Decentralized Deep Learning
Anis Elgabli, Jihong Park, Sabbir Ahmed +1
This article proposes a communication-efficient decentralized deep learning algorithm, coined layer-wise federated group ADMM (L-FGADMM). To minimize an empirical risk, every worke…
Downlink Performance of Dense Antenna Deployment: To Distribute or Concentrate?
Mounia Hamidouche, Ejder Baştuğ, Jihong Park +2
Massive multiple-input multiple-output (massive MIMO) and small cell densification are complementary key 5G enablers. Given a fixed number of the entire base-station antennas per u…
Remote UAV Online Path Planning via Neural Network Based Opportunistic Control
Hamid Shiri, Jihong Park, Mehdi Bennis
This letter proposes a neural network (NN) aided remote unmanned aerial vehicle (UAV) online control algorithm, coined oHJB. By downloading a UAV's state, a base station (BS) train…
Q-GADMM: Quantized Group ADMM for Communication Efficient Decentralized Machine Learning
Anis Elgabli, Jihong Park, Amrit S. Bedi +3
In this article, we propose a communication-efficient decentralized machine learning (ML) algorithm, coined quantized group ADMM (Q-GADMM). To reduce the number of communication li…
GADMM: Fast and Communication Efficient Framework for Distributed Machine Learning
Anis Elgabli, Jihong Park, Amrit S. Bedi +2
When the data is distributed across multiple servers, lowering the communication cost between the servers (or workers) while solving the distributed learning problem is an importan…
Distilling On-Device Intelligence at the Network Edge
Jihong Park, Shiqiang Wang, Anis Elgabli +6
Devices at the edge of wireless networks are the last mile data sources for machine learning (ML). As opposed to traditional ready-made public datasets, these user-generated privat…
Multi-hop Federated Private Data Augmentation with Sample Compression
Eunjeong Jeong, Seungeun Oh, Jihong Park +3
On-device machine learning (ML) has brought about the accessibility to a tremendous amount of data from the users while keeping their local data private instead of storing it in a…
Communication and Consensus Co-Design for Distributed, Low-Latency and Reliable Wireless Systems
Hyowoon Seo, Jihong Park, Mehdi Bennis +1
Designing distributed, fast and reliable wireless consensus protocols is instrumental in enabling mission-critical decentralized systems, such as robotic networks in the industrial…
Federated Reinforcement Distillation with Proxy Experience Memory
Han Cha, Jihong Park, Hyesung Kim +2
In distributed reinforcement learning, it is common to exchange the experience memory of each agent and thereby collectively train their local models. The experience memory, howeve…
Performance Analysis of Blockchain Systems with Wireless Mobile Miners
Gilsoo Lee, Jihong Park, Walid Saad +1
In this paper, a novel framework that uses wireless mobile miners (MMs) for computation purposes in a blockchain system is proposed. In the introduced system, the blockchain ledger…
Wireless Edge Computing with Latency and Reliability Guarantees
Mohammed S. Elbamby, Cristina Perfecto, Chen-Feng Liu +4
Edge computing is an emerging concept based on distributing computing, storage, and control services closer to end network nodes. Edge computing lies at the heart of the fifth gene…
Mobile XR over 5G: A way forward with mmWaves and Edge
Cristina Perfecto, Mohammed S. Elbamby, Jihong Park +2
This e-letter summarizes our most recent work and contributed approaches to increase the capacity, cut down on the latency and provide higher reliability in several extended realit…
Massive Autonomous UAV Path Planning: A Neural Network Based Mean-Field Game Theoretic Approach
Hamid Shiri, Jihong Park, Mehdi Bennis
This paper investigates the autonomous control of massive unmanned aerial vehicles (UAVs) for mission-critical applications (e.g., dispatching many UAVs from a source to a destinat…