Gerome Miklau | DeepAI

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Featured Co-authors

Andrew McCallum
110 publications
Tao Sun
57 publications
Dan Zhang
47 publications
Arya Mazumdar
45 publications
Philip S. Thomas
36 publications
Daniel Sheldon
31 publications
Julia Stoyanovich
30 publications
Ashwin Machanavajjhala
30 publications
H. V. Jagadish
28 publications
Ke Yang
25 publications
Abolfazl Asudeh
25 publications

∙ 12/08/2022

Tumult Analytics: a robust, easy-to-use, scalable, and expressive framework for differential privacy

In this short paper, we outline the design of Tumult Analytics, a Python...

0 Skye Berghel, et al. ∙

∙ 01/29/2022

AIM: An Adaptive and Iterative Mechanism for Differentially Private Synthetic Data

We propose AIM, a novel algorithm for differentially private synthetic d...

0 Ryan McKenna, et al. ∙

∙ 12/16/2021

Benchmarking Differentially Private Synthetic Data Generation Algorithms

This work presents a systematic benchmark of differentially private synt...

0 Yuchao Tao, et al. ∙

∙ 09/13/2021

Relaxed Marginal Consistency for Differentially Private Query Answering

Many differentially private algorithms for answering database queries in...

0 Ryan McKenna, et al. ∙

∙ 08/11/2021

Winning the NIST Contest: A scalable and general approach to differentially private synthetic data

We propose a general approach for differentially private synthetic data ...

0 Ryan McKenna, et al. ∙

∙ 07/22/2021

Differentially Private Algorithms for 2020 Census Detailed DHC Race & Ethnicity

This article describes a proposed differentially private (DP) algorithms...

0 Sam Haney, et al. ∙

∙ 06/23/2021

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

In this work we describe the High-Dimensional Matrix Mechanism (HDMM), a...

0 Ryan McKenna, et al. ∙

∙ 02/05/2020

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...

0 Ryan McKenna, et al. ∙

∙ 05/29/2019

Fair Decision Making using Privacy-Protected Data

Data collected about individuals is regularly used to make decisions tha...

0 Satya Kuppam, et al. ∙

∙ 02/01/2019

Privacy Preserving Off-Policy Evaluation

Many reinforcement learning applications involve the use of data that is...

0 Tengyang Xie, et al. ∙

∙ 01/26/2019

Graphical-model based estimation and inference for differential privacy

Many privacy mechanisms reveal high-level information about a data distr...

0 Ryan McKenna, et al. ∙

∙ 08/10/2018

Ektelo: A Framework for Defining Differentially-Private Computations

The adoption of differential privacy is growing but the complexity of de...

0 Dan Zhang, et al. ∙

∙ 08/10/2018

Optimizing error of high-dimensional statistical queries under differential privacy

Differentially private algorithms for answering sets of predicate counti...

0 Ryan McKenna, et al. ∙

∙ 04/29/2018

On Obtaining Stable Rankings

We often have to rank items with multiple attributes in a dataset. A typ...

0 Abolfazl Asudeh, et al. ∙

∙ 04/21/2018

A Nutritional Label for Rankings

Algorithmic decisions often result in scoring and ranking individuals to...

0 Ke Yang, et al. ∙

∙ 06/14/2017

Differentially Private Learning of Undirected Graphical Models using Collective Graphical Models

We investigate the problem of learning discrete, undirected graphical mo...

0 Garrett Bernstein, et al. ∙

∙ 05/11/2010

Scalable Probabilistic Databases with Factor Graphs and MCMC

Probabilistic databases play a crucial role in the management and unders...

0 Michael Wick, et al. ∙

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