8 papers
MUFFLe: Efficient Model Update Compression via Generalized Deduplication for Federated Learning
Xiaobo Zhao, Daniel E. Lucani
Federated learning is well suited to edge environments but is often limited by the uplink cost of transmitting model updates. This Work-in-Progress paper presents MUFFLe, a communi…
EntroGD: Scalable Generalized Deduplication for Efficient Direct Analytics on Compressed IoT Data
Xiaobo Zhao, Daniel E. Lucani
Massive data streams from IoT and cyber-physical systems must be processed under strict bandwidth, latency, and resource constraints. Generalized Deduplication (GD) is a promising…
Beampattern Synthesis for Discrete Phase RIS in Communication and Sensing Systems
Xiao Cai, Hei Victor Cheng, Daniel E. Lucani
Extensive research on Reconfigurable Intelligent Surfaces (RIS) has primarily focused on optimizing reflective coefficients for passive beamforming in specific target directions. T…
HyRES: A Hybrid Replication and Erasure Coding Approach to Data Storage
Daniel E. Lucani, Marcell Fehér
Reliability in distributed storage systems has typically focused on the design and deployment of data replication or erasure coding techniques. Although some scenarios have conside…
Touch-Augmented Gaussian Splatting for Enhanced 3D Scene Reconstruction
Yuchen Gao, Xiao Xu, Eckehard Steinbach +2
This paper presents a multimodal framework that integrates touch signals (contact points and surface normals) into 3D Gaussian Splatting (3DGS). Our approach enhances scene reconst…
dreaMLearning: Data Compression Assisted Machine Learning
Xiaobo Zhao, Aaron Hurst, Panagiotis Karras +1
Despite rapid advancements, machine learning, particularly deep learning, is hindered by the need for large amounts of labeled data to learn meaningful patterns without overfitting…