3 papers
cs.LG2025
Algorithmic Data Minimization for Machine Learning over Internet-of-Things Data Streams
Ted Shaowang, Shinan Liu, Jonatas Marques +2
Machine learning can analyze vast amounts of data generated by IoT devices to identify patterns, make predictions, and enable real-time decision-making. By processing sensor data,…
cs.NI2024
ServeFlow: A Fast-Slow Model Architecture for Network Traffic Analysis
Shinan Liu, Ted Shaowang, Gerry Wan +4
Network traffic analysis increasingly uses complex machine learning models as the internet consolidates and traffic gets more encrypted. However, over high-bandwidth networks, flow…
cs.DB2023
Quantifying Uncertainty in Aggregate Queries over Integrated Datasets
Deniz Turkcapar, Sanjay Krishnan
Data integration is a notoriously difficult and heuristic-driven process, especially when ground-truth data are not readily available. This paper presents a measure of uncertainty…