Juba Ziani

According to our database, Juba Ziani authored at least 32 papers between 2015 and 2024.

Collaborative distances:

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

2024

Algorithmic Collusion Without Threats.

Eshwar Ram Arunachaleswaran, Natalie Collina, Sampath Kannan, Aaron Roth, Juba Ziani

CoRR, 2024

Fairness Issues and Mitigations in (Differentially Private) Socio-demographic Data Processes.

Joonhyuk Ko, Juba Ziani, Saswat Das, Matt Williams, Ferdinando Fioretto

CoRR, 2024

Differentially Private Data Release on Graphs: Inefficiencies and Unfairness.

Ferdinando Fioretto, Diptangshu Sen, Juba Ziani

CoRR, 2024

On Rider Strategic Behavior in Ride-Sharing Platforms.

Jay Mulay, Diptangshu Sen, Juba Ziani

CoRR, 2024

Equilibria of Data Marketplaces with Privacy-Aware Sellers under Endogenous Privacy Costs.

Diptangshu Sen, Jingyan Wang, Juba Ziani

CoRR, 2024

Bayesian Strategic Classification.

Lee Cohen, Saeed Sharifi-Malvajerdi, Kevin Stangl, Ali Vakilian, Juba Ziani

CoRR, 2024

Personalized Differential Privacy for Ridge Regression.

Krishna Acharya, Franziska Boenisch, Rakshit Naidu, Juba Ziani

CoRR, 2024

Producers Equilibria and Dynamics in Engagement-Driven Recommender Systems.

Krishna Acharya, Varun Vangala, Jingyan Wang, Juba Ziani

CoRR, 2024

Oracle Efficient Algorithms for Groupwise Regret.

Krishna Acharya, Eshwar Ram Arunachaleswaran, Sampath Kannan, Aaron Roth, Juba Ziani

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Randomized Quantization is All You Need for Differential Privacy in Federated Learning.

Yeojoon Youn, Zihao Hu, Juba Ziani, Jacob D. Abernethy

CoRR, 2023

Optimal Data Acquisition with Privacy-Aware Agents.

Rachel Cummings, Hadi Elzayn, Emmanouil Pountourakis, Vasilis Gkatzelis, Juba Ziani

Proceedings of the 2023 IEEE Conference on Secure and Trustworthy Machine Learning, 2023

Wealth Dynamics Over Generations: Analysis and Interventions.

Krishna Acharya, Eshwar Ram Arunachaleswaran, Sampath Kannan, Aaron Roth, Juba Ziani

Proceedings of the 2023 IEEE Conference on Secure and Trustworthy Machine Learning, 2023

Sequential Strategic Screening.

Lee Cohen, Saeed Sharifi-Malvajerdi, Kevin Stangl, Ali Vakilian, Juba Ziani

Proceedings of the International Conference on Machine Learning, 2023

2022

Pipeline Interventions.

Eshwar Ram Arunachaleswaran, Sampath Kannan, Aaron Roth, Juba Ziani

Math. Oper. Res., November, 2022

The Privacy Paradox and Optimal Bias-Variance Trade-offs in Data Acquisition.

Guocheng Liao, Yu Su, Juba Ziani, Adam Wierman, Jianwei Huang

SIGMETRICS Perform. Evaluation Rev., 2022

Information Discrepancy in Strategic Learning.

Yahav Bechavod, Chara Podimata, Zhiwei Steven Wu, Juba Ziani

Proceedings of the International Conference on Machine Learning, 2022

2021

Algorithms and Learning for Fair Portfolio Design.

Emily Diana, Travis Dick, Hadi Elzayn, Michael Kearns, Aaron Roth, Zachary Schutzman, Saeed Sharifi-Malvajerdi, Juba Ziani

Proceedings of the EC '21: The 22nd ACM Conference on Economics and Computation, 2021

Gaming Helps! Learning from Strategic Interactions in Natural Dynamics.

Yahav Bechavod, Katrina Ligett, Zhiwei Steven Wu, Juba Ziani

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Third-Party Data Providers Ruin Simple Mechanisms.

Yang Cai, Federico Echenique, Hu Fu, Katrina Ligett, Adam Wierman, Juba Ziani

Proc. ACM Meas. Anal. Comput. Syst., 2020

Causal Feature Discovery through Strategic Modification.

Yahav Bechavod, Katrina Ligett, Zhiwei Steven Wu, Juba Ziani

CoRR, 2020

Differentially Private Call Auctions and Market Impact.

Emily Diana, Hadi Elzayn, Michael Kearns, Aaron Roth, Saeed Sharifi-Malvajerdi, Juba Ziani

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

2019

Data: Implications for Markets and for Society.

Juba Ziani

PhD thesis, 2019

Downstream Effects of Affirmative Action.

Sampath Kannan, Aaron Roth, Juba Ziani

Proceedings of the Conference on Fairness, Accountability, and Transparency, 2019

Access to Population-Level Signaling as a Source of Inequality.

Nicole Immorlica, Katrina Ligett, Juba Ziani

Proceedings of the Conference on Fairness, Accountability, and Transparency, 2019

2018

Datum: Managing Data Purchasing and Data Placement in a Geo-Distributed Data Market.

Xiaoqi Ren, Palma London, Juba Ziani, Adam Wierman

IEEE/ACM Trans. Netw., 2018

Optimal Data Acquisition for Statistical Estimation.

Yiling Chen, Nicole Immorlica, Brendan Lucier, Vasilis Syrgkanis, Juba Ziani

Proceedings of the 2018 ACM Conference on Economics and Computation, 2018

Non-Exploitable Protocols for Repeated Cake Cutting.

Omer Tamuz, Shai Vardi, Juba Ziani

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017

Inference on Auctions with Weak Assumptions on Information.

Vasilis Syrgkanis, Elie Tamer, Juba Ziani

CoRR, 2017

2016

Recovering Games from Perturbed Equilibrium Observations Using Convex Optimization.

Juba Ziani, Venkat Chandrasekaran, Katrina Ligett

CoRR, 2016

Joint Data Purchasing and Data Placement in a Geo-Distributed Data Market.

Xiaoqi Ren, Palma London, Juba Ziani, Adam Wierman

Proceedings of the 2016 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Science, 2016

2015

Cliques in the union of graphs.

Ron Aharoni, Eli Berger, Maria Chudnovsky, Juba Ziani

J. Comb. Theory B, 2015

Accuracy for Sale: Aggregating Data with a Variance Constraint.

Rachel Cummings, Katrina Ligett, Aaron Roth, Zhiwei Steven Wu, Juba Ziani

Proceedings of the 2015 Conference on Innovations in Theoretical Computer Science, 2015