21 citations · 46 across the 39 of their papers we have counts for
22 papers · 1 filter
Linear Last-Iterate Convergence Rates for Optimistic Learning in Harmonic Games
John Lazarsfeld, Anas Barakat, Jacob Abernethy +4
We prove that the last iterate of Optimistic Follow-The-Regularized-Leader (OFTRL) converges at a linear rate to a Nash equilibrium in multiplayer harmonic games. Our result holds…
Effort Matters in Score-Based Admissions: How Retaking and Aggregation Shape Test Scores
Christine Ling, Diptangshu Sen, Juba Ziani
Observed standardized test scores are the result of an endogenous process: students strategically allocate effort across multiple retake attempts to improve their outcomes. Because…
The Impact of Competition on Outcomes of Score-Based College Admissions
George Bentley, Diptangshu Sen, Juba Ziani
We study how the design of admissions policies affects the ability of students admitted to universities. In our model, applicants have a multi-dimensional ability, which is a combi…
Data Sharing with Endogenous Choices over Differential Privacy Levels
Raef Bassily, Kate Donahue, Diptangshu Sen +2
Motivated by the rapid push to decentralize sharing of data, we study whether large-scale data sharing coalitions can form in a decentralized manner under differential privacy when…
The Disparate Effects of Partial Information in Bayesian Strategic Learning
Srikanth Avasarala, Serena Wang, Juba Ziani
We study how partial information about scoring rules affects fairness in strategic learning settings. In strategic learning, a learner deploys a scoring rule, and agents respond st…
Incentivizing Desirable Effort Profiles in Strategic Classification: The Role of Causality and Uncertainty
Valia Efthymiou, Chara Podimata, Diptangshu Sen +1
We study strategic classification in binary decision-making settings where agents can modify their features in order to improve their classification outcomes. Importantly, our work…
Last-iterate Convergence for Symmetric, General-sum, Games Under The Exponential Weights Dynamic
Guanghui Wang, Krishna Acharya, Lokranjan Lakshmikanthan +2
We conduct a comprehensive analysis of the discrete-time exponential-weights dynamic with a constant step size on all general-sum and symmetric normal-form games, i.e.…
The Cost of Balanced Training-Data Production in an Online Data Market
Augustin Chaintreau, Roland Maio, Juba Ziani
Many ethical issues in machine learning are connected to the training data. Online data markets are an important source of training data, facilitating both production and distribut…
Algorithmic Collusion Without Threats
Eshwar Ram Arunachaleswaran, Natalie Collina, Sampath Kannan +2
There has been substantial recent concern that pricing algorithms might learn to ``collude.'' Supra-competitive prices can emerge as a Nash equilibrium of repeated pricing games, i…
On Rider Strategic Behavior in Ride-Sharing Platforms
Jay Mulay, Diptangshu Sen, Juba Ziani
Over the past decade, ride-sharing services have become increasingly important, with U.S. market leaders such as Uber and Lyft expanding to over 900 cities worldwide and facilitati…
Equilibria of Data Marketplaces with Privacy-Aware Sellers under Endogenous Privacy Costs
Diptangshu Sen, Jingyan Wang, Juba Ziani
We study a two-sided online data ecosystem comprised of an online platform, users on the platform, and downstream learners or data buyers. The learners can buy user data on the pla…
Producers Equilibria and Dynamics in Engagement-Driven Recommender Systems
Krishna Acharya, Varun Vangala, Jingyan Wang +1
Online platforms such as YouTube, Instagram heavily rely on recommender systems to decide what content to present to users. Producers, in turn, often create content that is likely…
Wealth Dynamics Over Generations: Analysis and Interventions
Krishna Acharya, Eshwar Ram Arunachaleswaran, Sampath Kannan +2
We present a stylized model with feedback loops for the evolution of a population's wealth over generations. Individuals have both talent and wealth: talent is a random variable di…
Optimal Data Acquisition with Privacy-Aware Agents
Rachel Cummings, Hadi Elzayn, Vasilis Gkatzelis +2
We study the problem faced by a data analyst or platform that wishes to collect private data from privacy-aware agents. To incentivize participation, in exchange for this data, the…
Information Discrepancy in Strategic Learning
Yahav Bechavod, Chara Podimata, Zhiwei Steven Wu +1
We initiate the study of the effects of non-transparency in decision rules on individuals' ability to improve in strategic learning settings. Inspired by real-life settings, such a…
Differentially Private Call Auctions and Market Impact
Emily Diana, Hadi Elzayn, Michael Kearns +3
We propose and analyze differentially private (DP) mechanisms for call auctions as an alternative to the complex and ad-hoc privacy efforts that are common in modern electronic mar…
Pipeline Interventions
Eshwar Ram Arunachaleswaran, Sampath Kannan, Aaron Roth +1
We introduce the \emph{pipeline intervention} problem, defined by a layered directed acyclic graph and a set of stochastic matrices governing transitions between successive layers.…
Access to Population-Level Signaling as a Source of Inequality
Nicole Immorlica, Katrina Ligett, Juba Ziani
We identify and explore differential access to population-level signaling (also known as information design) as a source of unequal access to opportunity. A population-level signal…
Downstream Effects of Affirmative Action
Sampath Kannan, Aaron Roth, Juba Ziani
We study a two-stage model, in which students are 1) admitted to college on the basis of an entrance exam which is a noisy signal about their qualifications (type), and then 2) tho…
Third-Party Data Providers Ruin Simple Mechanisms
Yang Cai, Federico Echenique, Hu Fu +3
Motivated by the growing prominence of third-party data providers in online marketplaces, this paper studies the impact of the presence of third-party data providers on mechanism d…
Optimal Data Acquisition for Statistical Estimation
Yiling Chen, Nicole Immorlica, Brendan Lucier +2
We consider a data analyst's problem of purchasing data from strategic agents to compute an unbiased estimate of a statistic of interest. Agents incur private costs to reveal their…
Efficiently characterizing games consistent with perturbed equilibrium observations
Juba Ziani, Venkat Chandrasekaran, Katrina Ligett
We study the problem of characterizing the set of games that are consistent with observed equilibrium play. Our contribution is to develop and analyze a new methodology based on co…