105 citations · 146 across the 8 of their papers we have counts for
10 papers
TESSERACT: Gradient Flip Score to Secure Federated Learning Against Model Poisoning Attacks
Atul Sharma, Wei Chen, Joshua Zhao +3
Federated learning---multi-party, distributed learning in a decentralized environment---is vulnerable to model poisoning attacks, even more so than centralized learning approaches.…
Federated Action Recognition on Heterogeneous Embedded Devices
Pranjal Jain, Shreyas Goenka, Saurabh Bagchi +2
Federated learning allows a large number of devices to jointly learn a model without sharing data. In this work, we enable clients with limited computing power to perform action re…
Ambrosia: Reduction in Data Transfer from Sensor to Server for Increased Lifetime of IoT Sensor Nodes
Shikhar Suryavansh, Abu Benna, Chris Guest +1
Data transmission accounts for significant energy consumption in wireless sensor networks where streaming data is generatedby the sensors. This impedes their use in many settings,…
JANUS: Benchmarking Commercial and Open-Source Cloud and Edge Platforms for Object and Anomaly Detection Workloads
Karthick Shankar, Pengcheng Wang, Ran Xu +2
With diverse IoT workloads, placing compute and analytics close to where data is collected is becoming increasingly important. We seek to understand what is the performance and the…
ApproxDet: Content and Contention-Aware Approximate Object Detection for Mobiles
Ran Xu, Chen-lin Zhang, Pengcheng Wang +5
Advanced video analytic systems, including scene classification and object detection, have seen widespread success in various domains such as smart cities and autonomous transporta…
Hybrid Low-Power Wide-Area Mesh Network for IoT Applications
Xiaofan Jiang, Heng zhang, Edgardo Alberto Barsallo Yi +6
The recent advancement of the Internet of Things (IoT) enables the possibility of data collection from diverse environments using IoT devices. However, despite the rapid advancemen…