79 citations · 221 across the 28 of their papers we have counts for
30 papers
Evaluating Learned Spatial Indexes
Sachith Pai, Jun Yang, Michael Mathioudakis
Learned indexes improve query performance by adapting search structures to data and workload distributions. Although many learned indexes have been proposed, their trade-offs remai…
Matching Meaning at Scale: Evaluating Semantic Search for 18th-Century Intellectual History through the Case of Locke
Yu Wu, Ananth Mahadevan, Filip Ginter +2
While digitized corpora have transformed the study of intellectual transmission, current methods rely heavily on lexical text reuse detection, capturing verbatim quotations but fun…
Optimizing a Data Science System for Text Reuse Analysis
Ananth Mahadevan, Michael Mathioudakis, Eetu Mäkelä +1
Text reuse is a methodological element of fundamental importance in humanities research: pieces of text that re-appear across different documents, verbatim or paraphrased, provide…
Cost-Effective Retraining of Machine Learning Models
Ananth Mahadevan, Michael Mathioudakis
It is important to retrain a machine learning (ML) model in order to maintain its performance as the data changes over time. However, this can be costly as it usually requires proc…
WaZI: A Learned and Workload-aware Z-Index
Sachith Pai, Michael Mathioudakis, Yanhao Wang
Learned indexes fit machine learning (ML) models to the data and use them to make query operations more time and space-efficient. Recent works propose using learned spatial indexes…
Max-Min Diversification with Fairness Constraints: Exact and Approximation Algorithms
Yanhao Wang, Michael Mathioudakis, Jia Li +1
Diversity maximization aims to select a diverse and representative subset of items from a large dataset. It is a fundamental optimization task that finds applications in data summa…