research
∙
09/04/2023
Secure and Efficient Federated Learning in LEO Constellations using Decentralized Key Generation and On-Orbit Model Aggregation
Satellite technologies have advanced drastically in recent years, leadin...
share
research
∙
08/11/2023
A Brain-Computer Interface Augmented Reality Framework with Auto-Adaptive SSVEP Recognition
Brain-Computer Interface (BCI) initially gained attention for developing...
research
∙
07/29/2023
Catching Elusive Depression via Facial Micro-Expression Recognition
Depression is a common mental health disorder that can cause consequenti...
research
∙
07/12/2023
YOGA: Deep Object Detection in the Wild with Lightweight Feature Learning and Multiscale Attention
We introduce YOGA, a deep learning based yet lightweight object detectio...
research
∙
07/09/2023
GNP Attack: Transferable Adversarial Examples via Gradient Norm Penalty
Adversarial examples (AE) with good transferability enable practical bla...
research
∙
05/21/2023
One-Shot Federated Learning for LEO Constellations that Reduces Convergence Time from Days to 90 Minutes
A Low Earth orbit (LEO) satellite constellation consists of a large numb...
research
∙
05/20/2023
LightESD: Fully-Automated and Lightweight Anomaly Detection Framework for Edge Computing
Anomaly detection is widely used in a broad range of domains from cybers...
research
∙
04/20/2023
Digital Twin Graph: Automated Domain-Agnostic Construction, Fusion, and Simulation of IoT-Enabled World
With the advances of IoT developments, copious sensor data are communica...
research
∙
03/22/2023
TSI-GAN: Unsupervised Time Series Anomaly Detection using Convolutional Cycle-Consistent Generative Adversarial Networks
Anomaly detection is widely used in network intrusion detection, autonom...
research
∙
02/27/2023
Optimizing Federated Learning in LEO Satellite Constellations via Intra-Plane Model Propagation and Sink Satellite Scheduling
The advances in satellite technology developments have recently seen a l...
research
∙
12/22/2022
AsyncFLEO: Asynchronous Federated Learning for LEO Satellite Constellations with High-Altitude Platforms
Low Earth Orbit (LEO) constellations, each comprising a large number of ...
research
∙
09/28/2022
Learning Deep Representations via Contrastive Learning for Instance Retrieval
Instance-level Image Retrieval (IIR), or simply Instance Retrieval, deal...
research
∙
08/14/2022
Long-Short History of Gradients is All You Need: Detecting Malicious and Unreliable Clients in Federated Learning
Federated learning offers a framework of training a machine learning mod...
research
∙
08/07/2022
No More Strided Convolutions or Pooling: A New CNN Building Block for Low-Resolution Images and Small Objects
Convolutional neural networks (CNNs) have made resounding success in man...
research
∙
08/24/2021
Data-Free Evaluation of User Contributions in Federated Learning
Federated learning (FL) trains a machine learning model on mobile device...
research
∙
08/09/2021
Adaptive Anomaly Detection for Internet of Things in Hierarchical Edge Computing: A Contextual-Bandit Approach
The advances in deep neural networks (DNN) have significantly enhanced r...
research
∙
09/11/2020
Coordinated Container Migration and Base Station Handover in Mobile Edge Computing
Offloading computationally intensive tasks from mobile users (MUs) to a ...
research
∙
04/15/2020
Contextual-Bandit Anomaly Detection for IoT Data in Distributed Hierarchical Edge Computing
Advances in deep neural networks (DNN) greatly bolster real-time detecti...
research
∙
01/10/2020
Adaptive Anomaly Detection for IoT Data in Hierarchical Edge Computing
Advances in deep neural networks (DNN) greatly bolster real-time detecti...
research
∙
12/18/2019
COBRA: Context-aware Bernoulli Neural Networks for Reputation Assessment
Trust and reputation management (TRM) plays an increasingly important ro...
research
∙
11/18/2019
Mechanism Design with Predicted Task Revenue for Bike Sharing Systems
Bike sharing systems have been widely deployed around the world in recen...
research
∙
12/12/2018
Distributed Anomaly Detection using Autoencoder Neural Networks in WSN for IoT
Wireless sensor networks (WSN) are fundamental to the Internet of Things...
research
∙
12/12/2018
An Efficient and Truthful Pricing Mechanism for Team Formation in Crowdsourcing Markets
In a crowdsourcing market, a requester is looking to form a team of work...
research
∙
12/12/2018
Optimal Prizes for All-Pay Contests in Heterogeneous Crowdsourcing
Incentives are key to the success of crowdsourcing which heavily depends...
research
∙
08/12/2018
WiFiScout: A Crowdsensing WiFi Advisory System with Gamification-based Incentive
As mobile crowdsensing techniques are steering many smart-city applicati...
research
∙
08/02/2018
The Privacy Exposure Problem in Mobile Location-based Services
Mobile location-based services (LBSs) empowered by mobile crowdsourcing ...
research
∙
09/10/2017