2 citations · 2 across the 3 of their papers we have counts for
3 papers
cs.LG2025
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…
eess.SP2025
Not all those who drift are lost: Drift correction and calibration scheduling for the IoT
Aaron Hurst, Andrey V. Kalinichev, Klaus Koren +1
Sensors provide a vital source of data that link digital systems with the physical world. However, as sensors age, the relationship between what they measure and what they output c…
cs.DB2023★ 2 cited
GreedyGD: Enhanced Generalized Deduplication for Direct Analytics in IoT
Aaron Hurst, Daniel E. Lucani, Qi Zhang
Exponential growth in the amount of data generated by the Internet of Things currently pose significant challenges for data communication, storage and analytics and leads to high c…