Umar Syed

Publication Activity (10 Years)

Years Active: 2003-2024
Publications (10 Years): 20

Top Topics

Marginal Utility

Differential Privacy

Top Venues

Publications

Enrico Bacis, Igor Bilogrevic, Róbert Busa-Fekete, Asanka Herath, Antonio Sartori, Umar Syed
Assessing Web Fingerprinting Risk. WWW (Companion Volume) (2024)
Kareem Amin, Alex Bie, Weiwei Kong, Alexey Kurakin, Natalia Ponomareva, Umar Syed, Andreas Terzis, Sergei Vassilvitskii
Private prediction for large-scale synthetic text generation. CoRR (2024)
Enrico Bacis, Igor Bilogrevic, Róbert Busa-Fekete, Asanka Herath, Antonio Sartori, Umar Syed
Assessing Web Fingerprinting Risk. CoRR (2024)
Jacob D. Abernethy, Robert E. Schapire, Umar Syed
Lexicographic Optimization: Algorithms and Stability. AISTATS (2024)
Alexey Kurakin, Natalia Ponomareva, Umar Syed, Liam MacDermed, Andreas Terzis
Harnessing large-language models to generate private synthetic text. CoRR (2023)
Gecia Bravo-Hermsdorff, Róbert Busa-Fekete, Mohammad Ghavamzadeh, Andres Muñoz Medina, Umar Syed
Private and Communication-Efficient Algorithms for Entropy Estimation. CoRR (2023)
Róbert Istvan Busa-Fekete, Andrés Muñoz Medina, Umar Syed, Sergei Vassilvitskii
Label differential privacy and private training data release. ICML (2023)
Gecia Bravo Hermsdorff, Róbert Busa-Fekete, Lee M. Gunderson, Andrés Muñoz Medina, Umar Syed
Statistical anonymity: Quantifying reidentification risks without reidentifying users. CoRR (2022)
Hossein Esfandiari, Vahab S. Mirrokni, Umar Syed, Sergei Vassilvitskii
Label differential privacy via clustering. AISTATS (2022)
Gecia Bravo-Hermsdorff, Róbert Busa-Fekete, Mohammad Ghavamzadeh, Andrés Muñoz Medina, Umar Syed
Private and Communication-Efficient Algorithms for Entropy Estimation. NeurIPS (2022)
Andrés Muñoz Medina, Umar Syed, Sergei Vassilvitskii, Ellen Vitercik
Private optimization without constraint violations. AISTATS (2021)
Alessandro Epasto, Andrés Muñoz Medina, Steven Avery, Yijian Bai, Róbert Busa-Fekete, C. J. Carey, Ya Gao, David Guthrie, Subham Ghosh, James Ioannidis, Junyi Jiao, Jakub Lacki, Jason Lee, Arne Mauser, Brian Milch, Vahab S. Mirrokni, Deepak Ravichandran, Wei Shi, Max Spero, Yunting Sun, Umar Syed, Sergei Vassilvitskii, Shuo Wang
Clustering for Private Interest-based Advertising. KDD (2021)
Hossein Esfandiari, Vahab S. Mirrokni, Umar Syed, Sergei Vassilvitskii
Label differential privacy via clustering. CoRR (2021)
Andrés Muñoz Medina, Umar Syed, Sergei Vassilvitskii, Ellen Vitercik
Private Optimization Without Constraint Violations. CoRR (2020)
Umar Syed
Inmate OS and VMM based Secured Virtualization for Cloud Encompassment. Int. J. Web Appl. 10 (1) (2018)
Eric Balkanski, Umar Syed, Sergei Vassilvitskii
Statistical Cost Sharing. CoRR (2017)
Umar Syed, Sergei Vassilvitskii
SQML: large-scale in-database machine learning with pure SQL. SoCC (2017)
Eric Balkanski, Umar Syed, Sergei Vassilvitskii
Statistical Cost Sharing. NIPS (2017)
Hoda Heidari, Mohammad Mahdian, Umar Syed, Sergei Vassilvitskii, Sadra Yazdanbod
Pricing a Low-regret Seller. ICML (2016)
Hamid Nazerzadeh, Renato Paes Leme, Afshin Rostamizadeh, Umar Syed
Where to Sell: Simulating Auctions From Learning Algorithms. EC (2016)
Krzysztof Marcin Choromanski, Afshin Rostamizadeh, Umar Syed
An Optimal Online Algorithm For Retrieving Heavily Perturbed Statistical Databases In The Low-Dimensional Querying Model. CIKM (2015)
Krzysztof Choromanski, Afshin Rostamizadeh, Umar Syed
An $\tilde{O}(\frac{1}{\sqrt{T}})$-error online algorithm for retrieving heavily perturbated statistical databases in the low-dimensional querying mode. CoRR (2015)
Giulia DeSalvo, Mehryar Mohri, Umar Syed
Learning with Deep Cascades. ALT (2015)
Corinna Cortes, Vitaly Kuznetsov, Mehryar Mohri, Umar Syed
Structural Maxent Models. ICML (2015)
Arthur Asuncion, Jac de Haan, Mehryar Mohri, Kayur Patel, Afshin Rostamizadeh, Umar Syed, Lauren Wong
Corporate learning at scale: lessons from a large online course at google. L@S (2014)
Kareem Amin, Afshin Rostamizadeh, Umar Syed
Repeated Contextual Auctions with Strategic Buyers. NIPS (2014)
Vitaly Kuznetsov, Mehryar Mohri, Umar Syed
Multi-Class Deep Boosting. NIPS (2014)
Corinna Cortes, Mehryar Mohri, Umar Syed
Deep Boosting. ICML (2014)
Kareem Amin, Afshin Rostamizadeh, Umar Syed
Learning Prices for Repeated Auctions with Strategic Buyers. CoRR (2013)
Kareem Amin, Afshin Rostamizadeh, Umar Syed
Learning Prices for Repeated Auctions with Strategic Buyers. NIPS (2013)
Kareem Amin, Michael J. Kearns, Umar Syed
Graphical Models for Bandit Problems CoRR (2012)
Umar Syed, Robert E. Schapire
Imitation Learning with a Value-Based Prior CoRR (2012)
Kareem Amin, Michael J. Kearns, Umar Syed
Graphical Models for Bandit Problems. UAI (2011)
Kareem Amin, Michael J. Kearns, Umar Syed
Bandits, Query Learning, and the Haystack Dimension. COLT (2011)
Alex Fabrikant, Umar Syed, Jennifer Rexford
There's something about MRAI: Timing diversity can exponentially worsen BGP convergence. INFOCOM (2011)
Umar Syed, Ben Taskar
Semi-Supervised Learning with Adversarially Missing Label Information. NIPS (2010)
Umar Syed, Aleksandrs Slivkins, Nina Mishra
Adapting to the Shifting Intent of Search Queries CoRR (2010)
Umar Syed, Robert E. Schapire
A Reduction from Apprenticeship Learning to Classification. NIPS (2010)
Mickey Brautbar, Michael J. Kearns, Umar Syed
Private and Third-Party Randomization in Risk-Sensitive Equilibrium Concepts. AAAI (2010)
Umar Syed, Aleksandrs Slivkins, Nina Mishra
Adapting to the Shifting Intent of Search Queries. NIPS (2009)
Umar Syed, Jason Williams
Using Automatically Transcribed Dialogs to Learn User Models in a Spoken Dialog System. ACL (2) (2008)
Umar Syed, Michael H. Bowling, Robert E. Schapire
Apprenticeship learning using linear programming. ICML (2008)
Umar Syed, Robert E. Schapire
A Game-Theoretic Approach to Apprenticeship Learning. NIPS (2007)
Umar Syed, Robert E. Schapire
Imitation Learning with a Value-Based Prior. UAI (2007)
Umar Syed, Golan Yona
Using a mixture of probabilistic decision trees for direct prediction of protein function. RECOMB (2003)