Black Bartholomew's Day

Appleby, David J.

doi:10.7228/manchester/9780719075612.001.0001

Cited by 3 publications

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“…Feature hashing is the process of using a hash function 15 to map features to indexes. It is sometimes referred to as "the hashing trick" 1,2 due to how it differs from traditional hashing: instead of using each hash as a key mapped to some value, the "trick" is that the hash itself is the value.…”

Section: Feature Hashingmentioning

confidence: 99%

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Hash the Universe: Differentially Private Text Extraction with Feature Hashing

Fletcher,

Roegiest,

Hudek

2024

Preprint

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Using artificial intelligence for text extraction can often require handling privacy-sensitive text. To avoid revealing confidential information, data owners and practitioners can use differential privacy, a definition of privacy with provable guarantees. In this work, we show how differential privacy can be applied to feature hashing. Feature hashing is a common technique for handling out-of-dictionary vocabulary, and for creating a lookup table to find feature weights in constant time. One of the special qualities of feature hashing is that all possible features are mapped to a discrete, finite output space. Our proposed technique takes advantage of this fact, and makes hashed feature sets Renyi-differentially private. The technique enables data owners to privatize any model that stores the data-dependent weights in a hash table, and provides protection against inference attacks on the model output. As a case study, we show how we have implemented our technique in commercial software that enables users to train text sequence classifiers on their own documents, and share the classifiers with other users without leaking training data. Results show that even common words can be protected with 0.06, 10^-5)-differential privacy, with only a 1% average reduction in Recall and no change in Precision.

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Section: Feature Hashingmentioning

confidence: 99%

“…We train Conditional Random Field models 34 using the Passive Aggressive algorithm 35 in the CRFSuite software 36 to find the relevant text. We use MurmurHash3 15 to perform the feature hashing, with a hash range of 𝑅 = 2 21 ≈ 2 × 10 6 .…”

Section: Case Studymentioning

confidence: 99%

Hash the Universe: Differentially Private Text Extraction with Feature Hashing

Fletcher,

Roegiest,

Hudek

2024

Preprint

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Believers’ Baptism, Commemoration and Communal Identity in Revolutionary England

Adcock¹

2020

Memory and the English Reformation

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Devotion and Polemic in Eighteenth-Century England: William Mason and the Literature of Lay Evangelical Anglicanism

Lewis¹

2019

Huntington Library Quarterly

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William Mason (1719-1791), an Anglican evangelical layman of Bermondsey, London, published extensively on theological issues to educate the Anglican laity in the Church of England's Reformed tradition. Despite the popularity of his writings, Mason has been neglected by scholars. By providing the first large-scale examination of Mason's works, Simon Lewis shows that eighteenth-century Calvinist evangelicalism benefited from an active and vocal laity, whose evangelistic strategies were not limited to preaching; provides a model for how scholars can integrate piety and polemic in their explorations of religious print culture; and enhances our understanding of the laity's engagement in theological controversies.

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Black Bartholomew's Day

Cited by 3 publications

References 0 publications

Hash the Universe: Differentially Private Text Extraction with Feature Hashing

Hash the Universe: Differentially Private Text Extraction with Feature Hashing

Believers’ Baptism, Commemoration and Communal Identity in Revolutionary England

Devotion and Polemic in Eighteenth-Century England: William Mason and the Literature of Lay Evangelical Anglicanism

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