Kareem Amin

39 papers A* 12A 4Journal 16Unranked 7
YearRankTypeTitle / Venue / Authors
2026 J jnl
Learning from Synthetic Data: Limitations of ERM.
CoRR
Kareem Amin, Alex Bie, Weiwei Kong, Umar Syed, Sergei Vassilvitskii
2025 J jnl
Clustering and Median Aggregation Improve Differentially Private Inference.
CoRR
Kareem Amin, Salman Avestimehr, Sara Babakniya, Alex Bie, Weiwei Kong, Natalia Ponomareva, Umar Syed
2025 J jnl
Escaping Collapse: The Strength of Weak Data for Large Language Model Training.
CoRR
Kareem Amin, Sara Babakniya, Alex Bie, Weiwei Kong, Umar Syed, Sergei Vassilvitskii
2024 J jnl
Practical Considerations for Differential Privacy.
CoRR
Kareem Amin, Alex Kulesza, Sergei Vassilvitskii
2024 — conf
Private prediction for large-scale synthetic text generation.
EMNLP (Findings)
Kareem Amin, Alex Bie, Weiwei Kong, Alexey Kurakin, Natalia Ponomareva, Umar Syed, Andreas Terzis, Sergei Vassilvitskii
2024 J jnl
Private prediction for large-scale synthetic text generation.
CoRR
Kareem Amin, Alex Bie, Weiwei Kong, Alexey Kurakin, Natalia Ponomareva, Umar Syed, Andreas Terzis, Sergei Vassilvitskii
2023 A* conf
Easy Differentially Private Linear Regression.
ICLR
Kareem Amin, Matthew Joseph, Mónica Ribero, Sergei Vassilvitskii
2023 A* conf
Learning-augmented private algorithms for multiple quantile release.
ICML
Mikhail Khodak, Kareem Amin, Travis Dick, Sergei Vassilvitskii
2022 J jnl
Easy Differentially Private Linear Regression.
CoRR
Kareem Amin, Matthew Joseph, Mónica Ribero, Sergei Vassilvitskii
2022 J jnl
Plume: Differential Privacy at Scale.
CoRR
Kareem Amin, Jennifer Gillenwater, Matthew Joseph, Alex Kulesza, Sergei Vassilvitskii
2022 J jnl
Private Algorithms with Private Predictions.
CoRR
Kareem Amin, Travis Dick, Mikhail Khodak, Sergei Vassilvitskii
2021 A* conf
Learning with Labeling Induced Abstentions.
NeurIPS
Kareem Amin, Giulia DeSalvo, Afshin Rostamizadeh
2021 A* conf
Learning with User-Level Privacy.
NeurIPS
Daniel Levy, Ziteng Sun, Kareem Amin, Satyen Kale, Alex Kulesza, Mehryar Mohri, Ananda Theertha Suresh
2021 J jnl
Learning with User-Level Privacy.
CoRR
Daniel Levy, Ziteng Sun, Kareem Amin, Satyen Kale, Alex Kulesza, Mehryar Mohri, Ananda Theertha Suresh
2020 A* conf
Pan-Private Uniformity Testing.
COLT
Kareem Amin, Matthew Joseph, Jieming Mao
2020 A conf
Understanding the Effects of Batching in Online Active Learning.
AISTATS
Kareem Amin, Corinna Cortes, Giulia DeSalvo, Afshin Rostamizadeh
2019 A* conf
Bounding User Contributions: A Bias-Variance Trade-off in Differential Privacy.
ICML
Kareem Amin, Alex Kulesza, Andres Muñoz Medina, Sergei Vassilvitskii
2019 A* conf
Differentially Private Covariance Estimation.
NeurIPS
Kareem Amin, Travis Dick, Alex Kulesza, Andres Muñoz Medina, Sergei Vassilvitskii
2019 J jnl
Pan-Private Uniformity Testing.
CoRR
Kareem Amin, Matthew Joseph, Jieming Mao
2017 — conf
Repeated Inverse Reinforcement Learning.
NIPS
Kareem Amin, Nan Jiang, Satinder Singh
2017 J jnl
Repeated Inverse Reinforcement Learning.
CoRR
Kareem Amin, Nan Jiang, Satinder Singh
2016 — conf
A moving target defense approach to mitigate DDoS attacks against proxy-based architectures.
CNS
Sridhar Venkatesan, Massimiliano Albanese, Kareem Amin, Sushil Jajodia, Mason Wright
2016 A conf
Gradient Methods for Stackelberg Games.
UAI
Kareem Amin, Michael P. Wellman, Satinder Singh
2016 A* conf
Strategic Payment Routing in Financial Credit Networks.
EC
Frank Cheng, Junming Liu, Kareem Amin, Michael P. Wellman
2016 — conf
Threshold Bandits, With and Without Censored Feedback.
NIPS
Jacob D. Abernethy, Kareem Amin, Ruihao Zhu
2016 J jnl
Towards Resolving Unidentifiability in Inverse Reinforcement Learning.
CoRR
Kareem Amin, Satinder Singh
2015 A* conf
Budgeted Prediction with Expert Advice.
AAAI
Kareem Amin, Satyen Kale, Gerald Tesauro, Deepak S. Turaga
2015 A* conf
Online Learning and Profit Maximization from Revealed Preferences.
AAAI
Kareem Amin, Rachel Cummings, Lili Dworkin, Michael J. Kearns, Aaron Roth
2014 A* conf
Learning from Contagion (Without Timestamps).
ICML
Kareem Amin, Hoda Heidari, Michael J. Kearns
2014 J jnl
Online Learning and Profit Maximization from Revealed Preferences.
CoRR
Kareem Amin, Rachel Cummings, Lili Dworkin, Michael J. Kearns, Aaron Roth
2014 — conf
Repeated Contextual Auctions with Strategic Buyers.
NIPS
Kareem Amin, Afshin Rostamizadeh, Umar Syed
2013 — conf
Large-Scale Bandit Problems and KWIK Learning.
ICML (1)
Jacob D. Abernethy, Kareem Amin, Michael J. Kearns, Moez Draief
2013 — conf
Learning Prices for Repeated Auctions with Strategic Buyers.
NIPS
Kareem Amin, Afshin Rostamizadeh, Umar Syed
2013 J jnl
Learning Prices for Repeated Auctions with Strategic Buyers.
CoRR
Kareem Amin, Afshin Rostamizadeh, Umar Syed
2012 J jnl
Budget Optimization for Sponsored Search: Censored Learning in MDPs
CoRR
Kareem Amin, Michael J. Kearns, Peter B. Key, Anton Schwaighofer
2012 A conf
Budget Optimization for Sponsored Search: Censored Learning in MDPs.
UAI
Kareem Amin, Michael J. Kearns, Peter B. Key, Anton Schwaighofer
2012 J jnl
Graphical Models for Bandit Problems
CoRR
Kareem Amin, Michael J. Kearns, Umar Syed
2011 A* conf
Bandits, Query Learning, and the Haystack Dimension.
COLT
Kareem Amin, Michael J. Kearns, Umar Syed
2011 A conf
Graphical Models for Bandit Problems.
UAI
Kareem Amin, Michael J. Kearns, Umar Syed