Maryam Aliakbarpour

Orcid: 0000-0001-5064-3221

According to our database1, Maryam Aliakbarpour authored at least 20 papers between 2016 and 2024.

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Bibliography

2024
Differentially Private Medians and Interior Points for Non-Pathological Data.
Proceedings of the 15th Innovations in Theoretical Computer Science Conference, 2024

Metalearning with Very Few Samples Per Task.
Proceedings of the Thirty Seventh Annual Conference on Learning Theory, June 30, 2024

2023
Metalearning with Very Few Samples Per Task.
CoRR, 2023

Hypothesis Selection with Memory Constraints.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Testing Tail Weight of a Distribution Via Hazard Rate.
Proceedings of the International Conference on Algorithmic Learning Theory, 2023

2022
Estimation of Entropy in Constant Space with Improved Sample Complexity.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021
Local Differential Privacy Is Equivalent to Contraction of E<sub>γ</sub>-Divergence.
CoRR, 2021

Local Differential Privacy Is Equivalent to Contraction of an $f$-Divergence.
Proceedings of the IEEE International Symposium on Information Theory, 2021

Rapid Approximate Aggregation with Distribution-Sensitive Interval Guarantees.
Proceedings of the 37th IEEE International Conference on Data Engineering, 2021

2020
Testing Determinantal Point Processes.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Testing Properties of Multiple Distributions with Few Samples.
Proceedings of the 11th Innovations in Theoretical Computer Science Conference, 2020

2019
Private Testing of Distributions via Sample Permutations.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Towards Testing Monotonicity of Distributions Over General Posets.
Proceedings of the Conference on Learning Theory, 2019

Testing Mixtures of Discrete Distributions.
Proceedings of the Conference on Learning Theory, 2019

2018
Sublinear-Time Algorithms for Counting Star Subgraphs via Edge Sampling.
Algorithmica, 2018

Differentially Private Identity and Equivalence Testing of Discrete Distributions.
Proceedings of the 35th International Conference on Machine Learning, 2018

2017
I've Seen "Enough": Incrementally Improving Visualizations to Support Rapid Decision Making.
Proc. VLDB Endow., 2017

Differentially Private Identity and Closeness Testing of Discrete Distributions.
CoRR, 2017

2016
Sublinear-Time Algorithms for Counting Star Subgraphs with Applications to Join Selectivity Estimation.
CoRR, 2016

Learning and Testing Junta Distributions.
Proceedings of the 29th Conference on Learning Theory, 2016


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