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Cost-aware Retraining for Machine Learning

Retraining a machine learning (ML) model is essential for maintaining its performance as the data change over time. However, retraining …

Ananth Mahadevan, Michael Mathioudakis
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A Comparative text similarity analysis of the works of Bernard Mandeville
Text similarity analysis entails studying identical and closely similar text passages across large corpora, with a particular focus on …
Yann Ryan, Ananth Mahadevan, Mikko Tolonen
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Reception Reader: Exploring Text Reuse in Early Modern British Publications
The Reception Reader is a web tool for studying text reuse in the Early English Books Online (EEBO-TCP) and Eighteenth Century …
David Rosson, Eetu Mäkelä, Ville Vaara, Ananth Mahadevan, Yann Ryan, Mikko Tolonen
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Reception Reader: Exploring Text Reuse in Early Modern British Publications
Scalably Using Node Attributes and Graph Structure for Node Classification
The task of node classification concerns a network where nodes are associated with labels, but labels are known only for some of the …
Arpit Merchant, Ananth Mahadevan, Michael Mathioudakis
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Certifiable Unlearning Pipelines for Logistic Regression: An Experimental Study
Machine unlearning is the task of updating machine learning (ML) models after a subset of the training data they were trained on is …
Ananth Mahadevan, Michael Mathioudakis
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Provable randomized rounding for minimum-similarity diversification
When searching for information in a data collection, we are often interested not only in finding relevant items, but also in assembling …
Bruno Ordozgiti, Ananth Mahadevan, Antonis Matakos, Aristides Gionis
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