7 citations · 19 across the 19 of their papers we have counts for
10 papers · 1 filter
GARV: Graph-Aware Refinement and Safety Verification for High-Level Robot Plans
Stabak Das, Priyesh Ranjan, Xiangfang Li +1
High-level robot actions such as goto(region) can hide intermediate traversal, allowing a monitor of the listed actions to accept a plan whose graph-level execution violates a safe…
Calibrated RF-Fingerprinting Under Interference With Heterogeneous Transmission Protocols
Tariq Abdul-Quddoos, Xiangfang Li, Lijun Qian
Radio Frequency(RF)-Fingerprinting is a spectrum monitoring technique that identifies specific transmitters based on hardware impairments imprinted within the emitted signal. Altho…
Multi-task GINN-LP for Multi-target Symbolic Regression
Hussein Rajabu, Lijun Qian, Xishuang Dong
In the area of explainable artificial intelligence, Symbolic Regression (SR) has emerged as a promising approach by discovering interpretable mathematical expressions that fit data…
Transmitter Identification and Protocol Categorization in Shared Spectrum via Multi-Task RF Classification at the Network Edge
Tariq Abdul-Quddoos, Tasnia Sharmin, Xiangfang Li +1
As spectrum sharing becomes increasingly vital to meet rising wireless demands in the future, spectrum monitoring and transmitter identification are indispensable for enforcing spe…
Data Augmentation via Diffusion Model to Enhance AI Fairness
Christina Hastings Blow, Lijun Qian, Camille Gibson +2
AI fairness seeks to improve the transparency and explainability of AI systems by ensuring that their outcomes genuinely reflect the best interests of users. Data augmentation, whi…
Comprehensive Validation on Reweighting Samples for Bias Mitigation via AIF360
Christina Hastings Blow, Lijun Qian, Camille Gibson +2
Fairness AI aims to detect and alleviate bias across the entire AI development life cycle, encompassing data curation, modeling, evaluation, and deployment-a pivotal aspect of ethi…
Effect of Batch Normalization on Noise Resistant Property of Deep Learning Models
Omobayode Fagbohungbe, Lijun Qian
The fast execution speed and energy efficiency of analog hardware has made them a strong contender for deployment of deep learning model at the edge. However, there are concerns ab…
Impact of Learning Rate on Noise Resistant Property of Deep Learning Models
Omobayode Fagbohungbe, Lijun Qian
The interest in analog computation has grown tremendously in recent years due to its fast computation speed and excellent energy efficiency, which is very important for edge and Io…
Impact of L1 Batch Normalization on Analog Noise Resistant Property of Deep Learning Models
Omobayode Fagbohungbe, Lijun Qian
Analog hardware has become a popular choice for machine learning on resource-constrained devices recently due to its fast execution and energy efficiency. However, the inherent pre…
Integrating Human-in-the-loop into Swarm Learning for Decentralized Fake News Detection
Xishuang Dong, Lijun Qian
Social media has become an effective platform to generate and spread fake news that can mislead people and even distort public opinion. Centralized methods for fake news detection,…