Gerome Miklau

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University of Massachusetts Amherst

Differentially Private Algorithms for 2020 Census Detailed DHC Race & Ethnicity

This article describes a proposed differentially private (DP) algorithms...
07/22/2021 ∙ by Sam Haney, et al. ∙ 0 ∙ share

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HDMM: Optimizing error of high-dimensional statistical queries under differential privacy

In this work we describe the High-Dimensional Matrix Mechanism (HDMM), a...
06/23/2021 ∙ by Ryan McKenna, et al. ∙ 0 ∙ share

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A workload-adaptive mechanism for linear queries under local differential privacy

We propose a new mechanism to accurately answer a user-provided set of l...
02/05/2020 ∙ by Ryan McKenna, et al. ∙ 0 ∙ share

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Fair Decision Making using Privacy-Protected Data

Data collected about individuals is regularly used to make decisions tha...
05/29/2019 ∙ by Satya Kuppam, et al. ∙ 0 ∙ share

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Privacy Preserving Off-Policy Evaluation

Many reinforcement learning applications involve the use of data that is...
02/01/2019 ∙ by Tengyang Xie, et al. ∙ 0 ∙ share

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Graphical-model based estimation and inference for differential privacy

Many privacy mechanisms reveal high-level information about a data distr...
01/26/2019 ∙ by Ryan McKenna, et al. ∙ 0 ∙ share

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Ektelo: A Framework for Defining Differentially-Private Computations

The adoption of differential privacy is growing but the complexity of de...
08/10/2018 ∙ by Dan Zhang, et al. ∙ 0 ∙ share

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Optimizing error of high-dimensional statistical queries under differential privacy

Differentially private algorithms for answering sets of predicate counti...
08/10/2018 ∙ by Ryan McKenna, et al. ∙ 0 ∙ share

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On Obtaining Stable Rankings

We often have to rank items with multiple attributes in a dataset. A typ...
04/29/2018 ∙ by Abolfazl Asudeh, et al. ∙ 0 ∙ share

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A Nutritional Label for Rankings

Algorithmic decisions often result in scoring and ranking individuals to...
04/21/2018 ∙ by Ke Yang, et al. ∙ 0 ∙ share

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Differentially Private Learning of Undirected Graphical Models using Collective Graphical Models

We investigate the problem of learning discrete, undirected graphical mo...
06/14/2017 ∙ by Garrett Bernstein, et al. ∙ 0 ∙ share

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Scalable Probabilistic Databases with Factor Graphs and MCMC

Probabilistic databases play a crucial role in the management and unders...
05/11/2010 ∙ by Michael Wick, et al. ∙ 0 ∙ share

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Gerome Miklau

Featured Co-authors

Andrew McCallum

Tao Sun

Arya Mazumdar

Philip S. Thomas

Daniel Sheldon

H. V. Jagadish

Ashwin Machanavajjhala

Julia Stoyanovich

Bill Howe

Dan Zhang

Ke Yang

Differentially Private Algorithms for 2020 Census Detailed DHC Race & Ethnicity

HDMM: Optimizing error of high-dimensional statistical queries under differential privacy

A workload-adaptive mechanism for linear queries under local differential privacy

Fair Decision Making using Privacy-Protected Data

Privacy Preserving Off-Policy Evaluation

Graphical-model based estimation and inference for differential privacy

Ektelo: A Framework for Defining Differentially-Private Computations

Optimizing error of high-dimensional statistical queries under differential privacy

On Obtaining Stable Rankings

A Nutritional Label for Rankings

Differentially Private Learning of Undirected Graphical Models using Collective Graphical Models

Scalable Probabilistic Databases with Factor Graphs and MCMC