Themis Palpanas

Progressive Data Science: Potential and Challenges

2018 · arXiv (Cornell University)

Data science requires time-consuming iterative manual activities. In particular, activities such as data selection, preprocessing, transformation, and mining, highly depend on iterative trial-and-error processes that could be sped-up significantly by providing quick feedback on the …

SAND in action

2021 · Proceedings of the VLDB Endowment

Subsequence anomaly detection in long data series is a significant problem. While the demand for real-time analytics and decision making increases, anomaly detection methods have to operate over streams and handle drifts in data distribution. …

Volume under the surface

2022 · Proceedings of the VLDB Endowment

Anomaly detection (AD) is a fundamental task for time-series analytics with important implications for the downstream performance of many applications. In contrast to other domains where AD mainly focuses on point-based anomalies (i.e., outliers in …