Ariel Schvartzman

According to our database, Ariel Schvartzman authored at least 19 papers between 2016 and 2024.

Collaborative distances:

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

2024

Auto-Bidding and Auctions in Online Advertising: A Survey.

Gagan Aggarwal, Ashwinkumar Badanidiyuru, Santiago R. Balseiro, Kshipra Bhawalkar, Yuan Deng, Zhe Feng, Gagan Goel, Christopher Liaw, Haihao Lu, Mohammad Mahdian, Jieming Mao, Aranyak Mehta, Vahab Mirrokni, Renato Paes Leme, Andrés Perlroth, Georgios Piliouras, Jon Schneider, Ariel Schvartzman, Balasubramanian Sivan, Kelly Spendlove, Yifeng Teng, Di Wang, Hanrui Zhang, Mingfei Zhao, Wennan Zhu, Song Zuo

SIGecom Exch., 2024

Platform Competition in the Autobidding World.

Gagan Aggarwal, Andrés Perlroth, Ariel Schvartzman, Mingfei Zhao

CoRR, 2024

Toward Fair and Strategyproof Tournament Rules for Tournaments with Partially Transferable Utilities.

David M. Pennock, Ariel Schvartzman, Eric Xue

Proceedings of the Algorithmic Decision Theory - 8th International Conference, 2024

On Approximately Strategy-Proof Tournament Rules for Collusions of Size at Least Three.

David Miksaník, Ariel Schvartzman, Jan Soukup

Proceedings of the Algorithmic Decision Theory - 8th International Conference, 2024

2023

Fine-Grained Buy-Many Mechanisms Are Not Much Better Than Bundling.

Sepehr Assadi, Vikram Kher, George Li, Ariel Schvartzman

Proceedings of the 24th ACM Conference on Economics and Computation, 2023

2022

Fine-Grained Buy-Many Mechanisms Are Not Much Better Than Bundling.

Sepehr Assadi, Ariel Schvartzman

CoRR, 2022

On Infinite Separations Between Simple and Optimal Mechanisms.

Alexandros Psomas, Ariel Schvartzman, S. Matthew Weinberg

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2020

Circumventing Lower Bounds in Mechanism and Tournament Design

Ariel Schvartzman

PhD thesis, 2020

Optimal Mechanism Design for Single-Minded Agents.

Nikhil R. Devanur, Kira Goldner, Raghuvansh R. Saxena, Ariel Schvartzman, S. Matthew Weinberg

Proceedings of the EC '20: The 21st ACM Conference on Economics and Computation, 2020

Approximately Strategyproof Tournament Rules: On Large Manipulating Sets and Cover-Consistence.

Ariel Schvartzman, S. Matthew Weinberg, Eitan Zlatin, Albert Zuo

Proceedings of the 11th Innovations in Theoretical Computer Science Conference, 2020

2019

Approximation Schemes for a Buyer with Independent Items via Symmetries.

Pravesh Kothari, Divyarthi Mohan, Ariel Schvartzman, Sahil Singla, S. Matthew Weinberg

CoRR, 2019

Approximation Schemes for a Unit-Demand Buyer with Independent Items via Symmetries.

Pravesh Kothari, Sahil Singla, Divyarthi Mohan, Ariel Schvartzman, S. Matthew Weinberg

Proceedings of the 60th IEEE Annual Symposium on Foundations of Computer Science, 2019

Smoothed Analysis of Multi-Item Auctions with Correlated Values.

Alexandros Psomas, Ariel Schvartzman, S. Matthew Weinberg

Proceedings of the 2019 ACM Conference on Economics and Computation, 2019

2018

The fewest clues problem.

Erik D. Demaine, Fermi Ma, Ariel Schvartzman, Erik Waingarten, Scott Aaronson

Theor. Comput. Sci., 2018

The menu complexity of "one-and-a-half-dimensional" mechanism design.

Raghuvansh R. Saxena, Ariel Schvartzman, S. Matthew Weinberg

Proceedings of the Twenty-Ninth Annual ACM-SIAM Symposium on Discrete Algorithms, 2018

2017

Bounds for the Communication Complexity of Two-Player Approximate Correlated Equilibria.

Young Kun-Ko, Ariel Schvartzman

Electron. Colloquium Comput. Complex., 2017

Condorcet-Consistent and Approximately Strategyproof Tournament Rules.

Jon Schneider, Ariel Schvartzman, S. Matthew Weinberg

Proceedings of the 8th Innovations in Theoretical Computer Science Conference, 2017

Coding in Undirected Graphs Is Either Very Helpful or Not Helpful at All.

Mark Braverman, Sumegha Garg, Ariel Schvartzman

Proceedings of the 8th Innovations in Theoretical Computer Science Conference, 2017

2016

Network coding in undirected graphs is either very helpful or not helpful at all.

Mark Braverman, Sumegha Garg, Ariel Schvartzman

CoRR, 2016