Publications (6)
Certifiable Machine Unlearning for Linear Models
Ananth Mahadevan, Michael Mathioudakis
Machine unlearning is the task of updating machine learning (ML) models after a subset of the training data they were trained on is deleted. Methods for the task are desired to com…
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…
Reception Reader: Exploring Text Reuse in Early Modern British Publications
David Rosson, Eetu Mäkelä, Ville Vaara +3
The Reception Reader is a web tool for studying text reuse in the Early English Books Online (EEBO-TCP) and Eighteenth Century Collections Online (ECCO) data. Users can: 1) explore…
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…
PhiPlot: A Web-Based Interactive EDA Environment for Atmospherically Relevant Molecules
Matias Loukojärvi, Ananth Mahadevan, Katsiaryna Haitsiukevich +1
Advances in computational chemistry have produced high-dimensional datasets on atmospherically relevant molecules. To aid exploration of such datasets, particularly for the study o…
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…