Kareem Amin - RankMe

39 papers A* 12A 4Journal 16Unranked 7

Year	Rank	Type	Title / 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