4 citations · 7 across the 5 of their papers we have counts for
5 papers
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…
Highly Efficient Direct Analytics on Semantic-aware Time Series Data Compression
Guoyou Sun, Panagiotis Karras, Qi Zhang
Semantic communication has emerged as a promising paradigm to tackle the challenges of massive growing data traffic and sustainable data communication. It shifts the focus from dat…
SHRINK: Data Compression by Semantic Extraction and Residuals Encoding
Guoyou Sun, Panagiotis Karras, Qi Zhang
The distributed data infrastructure in Internet of Things (IoT) ecosystems requires efficient data-series compression methods, along with the ability to feed different accuracy dem…
An autoencoder for compressing angle-resolved photoemission spectroscopy data
Steinn Ymir Agustsson, Mohammad Ahsanul Haque, Thi Tam Truong +5
Angle-resolved photoemission spectroscopy (ARPES) is a powerful experimental technique to determine the electronic structure of solids. Advances in light sources for ARPES experime…
Data-driven prediction of tool wear using Bayesian-regularized artificial neural networks
Tam T. Truong, Jay Airao, Panagiotis Karras +3
The prediction of tool wear helps minimize costs and enhance product quality in manufacturing. While existing data-driven models using machine learning and deep learning have contr…