Kareem Amin

According to our database, Kareem Amin authored at least 27 papers between 2011 and 2024.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of three.

2024

Practical Considerations for Differential Privacy.

Kareem Amin, Alex Kulesza, Sergei Vassilvitskii

CoRR, 2024

Private prediction for large-scale synthetic text generation.

Kareem Amin, Alex Bie, Weiwei Kong, Alexey Kurakin, Natalia Ponomareva, Umar Syed, Andreas Terzis, Sergei Vassilvitskii

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

2023

Learning-augmented private algorithms for multiple quantile release.

Mikhail Khodak, Kareem Amin, Travis Dick, Sergei Vassilvitskii

Proceedings of the International Conference on Machine Learning, 2023

Easy Differentially Private Linear Regression.

Kareem Amin, Matthew Joseph, Mónica Ribero, Sergei Vassilvitskii

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Private Algorithms with Private Predictions.

Kareem Amin, Travis Dick, Mikhail Khodak, Sergei Vassilvitskii

CoRR, 2022

Plume: Differential Privacy at Scale.

Kareem Amin, Jennifer Gillenwater, Matthew Joseph, Alex Kulesza, Sergei Vassilvitskii

CoRR, 2022

2021

Learning with User-Level Privacy.

Daniel Levy, Ziteng Sun, Kareem Amin, Satyen Kale, Alex Kulesza, Mehryar Mohri, 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.

Kareem Amin, Giulia DeSalvo, 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.

Kareem Amin, Matthew Joseph, Jieming Mao

Proceedings of the Conference on Learning Theory, 2020

Understanding the Effects of Batching in Online Active Learning.

Kareem Amin, Corinna Cortes, Giulia DeSalvo, Afshin Rostamizadeh

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

2019

Differentially Private Covariance Estimation.

Kareem Amin, Travis Dick, Alex Kulesza, Andres Muñoz Medina, 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.

Kareem Amin, Alex Kulesza, Andres Muñoz Medina, Sergei Vassilvitskii

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

2017

Repeated Inverse Reinforcement Learning.

Kareem Amin, Nan Jiang, Satinder Singh

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.

Kareem Amin, Satinder Singh

CoRR, 2016

Gradient Methods for Stackelberg Games.

Kareem Amin, Michael P. Wellman, Satinder Singh

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

Strategic Payment Routing in Financial Credit Networks.

Frank Cheng, Junming Liu, Kareem Amin, Michael P. Wellman

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

Threshold Bandits, With and Without Censored Feedback.

Jacob D. Abernethy, Kareem Amin, Ruihao Zhu

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.

Sridhar Venkatesan, Massimiliano Albanese, Kareem Amin, Sushil Jajodia, Mason Wright

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

2015

Budgeted Prediction with Expert Advice.

Kareem Amin, Satyen Kale, Gerald Tesauro, Deepak S. Turaga

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

Online Learning and Profit Maximization from Revealed Preferences.

Kareem Amin, Rachel Cummings, Lili Dworkin, Michael J. Kearns, Aaron Roth

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

2014

Repeated Contextual Auctions with Strategic Buyers.

Kareem Amin, Afshin Rostamizadeh, Umar Syed

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

Learning from Contagion (Without Timestamps).

Kareem Amin, Hoda Heidari, Michael J. Kearns

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

2013

Learning Prices for Repeated Auctions with Strategic Buyers.

Kareem Amin, Afshin Rostamizadeh, Umar Syed

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.

Jacob D. Abernethy, Kareem Amin, Michael J. Kearns, Moez Draief

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

2012

Budget Optimization for Sponsored Search: Censored Learning in MDPs.

Kareem Amin, Michael J. Kearns, Peter B. Key, Anton Schwaighofer

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

2011

Bandits, Query Learning, and the Haystack Dimension.

Kareem Amin, Michael J. Kearns, Umar Syed

Proceedings of the COLT 2011, 2011

Graphical Models for Bandit Problems.

Kareem Amin, Michael J. Kearns, Umar Syed

Proceedings of the UAI 2011, 2011