Explaining Aggregates for Exploratory Analytics. - Fotis Savva; Christos Anagnostopoulos 001; Peter Triantafillou (IEEE BigData, 2018)

Scalable aggregation predictive analytics - A query-driven machine learning approach. - Christos Anagnostopoulos 001; Fotis Savva; Peter Triantafillou (Appl. Intell., 2018)

Aggregate Query Prediction under Dynamic Workloads. - Fotis Savva; Christos Anagnostopoulos 001; Peter Triantafillou (IEEE BigData, 2019)

Query-Driven Learning for Next Generation Predictive Modeling & Analytics. - Fotis Savva (SIGMOD Conference, 2019)

SuRF: Identification of Interesting Data Regions with Surrogate Models. - Fotis Savva; Christos Anagnostopoulos 001; Peter Triantafillou (ICDE, 2020)

ML-AQP: Query-Driven Approximate Query Processing based on Machine Learning. - Fotis Savva; Christos Anagnostopoulos 001; Peter Triantafillou (CoRR, 2020)

Adaptive learning of aggregate analytics under dynamic workloads. - Fotis Savva; Christos Anagnostopoulos 001; Peter Triantafillou (Future Gener. Comput. Syst., 2020)

Large-scale Data Exploration Using Explanatory Regression Functions. - Fotis Savva; Christos Anagnostopoulos 001; Peter Triantafillou; Kostas Kolomvatsos (ACM Trans. Knowl. Discov. Data, 2020)

TSMF: Network Latency Estimation using Matrix Factorization and Time Series Forecasting. - Fotis Savva; Christos Anagnostopoulos 001; Dimitrios Pezaros (Networking, 2021)

Query-driven learning for automating exploratory analytics in large-scale data management systems. - Fotis Savva (2021)