We stand with Ukraine

We stand with Ukraine

Kareem Amin

Affiliations:

Google Research, New York, NY, USA
University of Michigan, USA (former)
University of Pennsylvania, Philadelphia, PA, USA (Ph.D)

According to our database¹, Kareem Amin authored at least 25 papers between 2011 and 2023.

Collaborative distances:

Dijkstra number² of three.
Erdős number³ of three.

Timeline

Legend:

Book

In proceedings

Article

PhD thesis

Dataset

Other

Links

Online presence:

on amin.kareemx.com

On csauthors.net:

Bibliography

2023

Learning-augmented private algorithms for multiple quantile release.

[BibT_eX]

[DOI]

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Sergei Vassilvitskii

Proceedings of the International Conference on Machine Learning, 2023

Easy Differentially Private Linear Regression.

[BibT_eX]

[DOI]

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Sergei Vassilvitskii

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Private Algorithms with Private Predictions.

[BibT_eX]

[DOI]

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Sergei Vassilvitskii

CoRR, 2022

Plume: Differential Privacy at Scale.

[BibT_eX]

[DOI]

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Jennifer Gillenwater

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,

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Sergei Vassilvitskii

CoRR, 2022

2021

Learning with User-Level Privacy.

[BibT_eX]

[DOI]

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Ananda Theertha Suresh

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Learning with Labeling Induced Abstentions.

[BibT_eX]

[DOI]

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Afshin Rostamizadeh

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

Pan-Private Uniformity Testing.

[BibT_eX]

[DOI]

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Proceedings of the Conference on Learning Theory, 2020

Understanding the Effects of Batching in Online Active Learning.

[BibT_eX]

[DOI]

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Afshin Rostamizadeh

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Differentially Private Covariance Estimation.

[BibT_eX]

[DOI]

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,

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Andres Muñoz Medina

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Sergei Vassilvitskii

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Bounding User Contributions: A Bias-Variance Trade-off in Differential Privacy.

[BibT_eX]

[DOI]

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Andres Muñoz Medina

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Sergei Vassilvitskii

Proceedings of the 36th International Conference on Machine Learning, 2019

2017

Repeated Inverse Reinforcement Learning.

[BibT_eX]

[DOI]

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Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

2016

Towards Resolving Unidentifiability in Inverse Reinforcement Learning.

[BibT_eX]

[DOI]

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CoRR, 2016

Gradient Methods for Stackelberg Games.

[BibT_eX]

[DOI]

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Michael P. Wellman

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Proceedings of the Thirty-Second Conference on Uncertainty in Artificial Intelligence, 2016

Strategic Payment Routing in Financial Credit Networks.

[BibT_eX]

[DOI]

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Michael P. Wellman

Proceedings of the 2016 ACM Conference on Economics and Computation, 2016

Threshold Bandits, With and Without Censored Feedback.

[BibT_eX]

[DOI]

Jacob D. Abernethy

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Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

A moving target defense approach to mitigate DDoS attacks against proxy-based architectures.

[BibT_eX]

[DOI]

Sridhar Venkatesan

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Massimiliano Albanese

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Proceedings of the 2016 IEEE Conference on Communications and Network Security, 2016

2015

Budgeted Prediction with Expert Advice.

[BibT_eX]

[DOI]

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Deepak S. Turaga

Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

Online Learning and Profit Maximization from Revealed Preferences.

[BibT_eX]

[DOI]

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Rachel Cummings

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,

Michael J. Kearns

,

Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2014

Repeated Contextual Auctions with Strategic Buyers.

[BibT_eX]

[DOI]

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Afshin Rostamizadeh

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Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Learning from Contagion (Without Timestamps).

[BibT_eX]

[DOI]

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Michael J. Kearns

Proceedings of the 31th International Conference on Machine Learning, 2014

2013

Learning Prices for Repeated Auctions with Strategic Buyers.

[BibT_eX]

[DOI]

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Afshin Rostamizadeh

,

Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Large-Scale Bandit Problems and KWIK Learning.

[BibT_eX]

[DOI]

Jacob D. Abernethy

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,

Michael J. Kearns

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Proceedings of the 30th International Conference on Machine Learning, 2013

2012

Budget Optimization for Sponsored Search: Censored Learning in MDPs.

[BibT_eX]

[DOI]

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Michael J. Kearns

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,

Anton Schwaighofer

Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence, 2012

2011

Bandits, Query Learning, and the Haystack Dimension.

[BibT_eX]

[DOI]

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Michael J. Kearns

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Proceedings of the COLT 2011, 2011

Graphical Models for Bandit Problems.

[BibT_eX]

[DOI]

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Michael J. Kearns

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Proceedings of the UAI 2011, 2011

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