activity
20172020
most citedDifferentially Private Identity and Closeness Testing of Discrete Distributions

10 citations · 10 across the 6 of their papers we have counts for

collaborators

6 papers

cs.DB2020

Rapid Approximate Aggregation with Distribution-Sensitive Interval Guarantees

Stephen Macke, Maryam Aliakbarpour, Ilias Diakonikolas +2

Aggregating data is fundamental to data analytics, data exploration, and OLAP. Approximate query processing (AQP) techniques are often used to accelerate computation of aggregates…

cs.LG2020

Testing Determinantal Point Processes

Khashayar Gatmiry, Maryam Aliakbarpour, Stefanie Jegelka

Determinantal point processes (DPPs) are popular probabilistic models of diversity. In this paper, we investigate DPPs from a new perspective: property testing of distributions. Gi…

cs.DS2019

Testing Properties of Multiple Distributions with Few Samples

Maryam Aliakbarpour, Sandeep Silwal

We propose a new setting for testing properties of distributions while receiving samples from several distributions, but few samples per distribution. Given samples from distri…

math.ST2019

Testing Mixtures of Discrete Distributions

Maryam Aliakbarpour, Ravi Kumar, Ronitt Rubinfeld

There has been significant study on the sample complexity of testing properties of distributions over large domains. For many properties, it is known that the sample complexity can…

cs.DS2019

Towards Testing Monotonicity of Distributions Over General Posets

Maryam Aliakbarpour, Themis Gouleakis, John Peebles +2

In this work, we consider the sample complexity required for testing the monotonicity of distributions over partial orders. A distribution over a poset is monotone if, for any…

cs.LG201710 cited

Differentially Private Identity and Closeness Testing of Discrete Distributions

Maryam Aliakbarpour, Ilias Diakonikolas, Ronitt Rubinfeld

We investigate the problems of identity and closeness testing over a discrete population from random samples. Our goal is to develop efficient testers while guaranteeing Differenti…