8 citations · 29 across the 13 of their papers we have counts for
16 papers
Human vs. Generative AI in Content Creation Competition: Symbiosis or Conflict?
Fan Yao, Chuanhao Li, Denis Nekipelov +2
The advent of generative AI (GenAI) technology produces transformative impact on the content creation landscape, offering alternative approaches to produce diverse, high-quality co…
Sharp and Robust Estimation of Partially Identified Discrete Response Models
Shakeeb Khan, Tatiana Komarova, Denis Nekipelov
Semiparametric discrete choice models are widely used in a variety of practical applications. While these models are point identified in the presence of continuous covariates, they…
How Bad is Top- Recommendation under Competing Content Creators?
Fan Yao, Chuanhao Li, Denis Nekipelov +2
Content creators compete for exposure on recommendation platforms, and such strategic behavior leads to a dynamic shift over the content distribution. However, how the creators' co…
Learning from a Learning User for Optimal Recommendations
Fan Yao, Chuanhao Li, Denis Nekipelov +2
In real-world recommendation problems, especially those with a formidably large item space, users have to gradually learn to estimate the utility of any fresh recommendations from…
Learning the Optimal Recommendation from Explorative Users
Fan Yao, Chuanhao Li, Denis Nekipelov +2
We propose a new problem setting to study the sequential interactions between a recommender system and a user. Instead of assuming the user is omniscient, static, and explicit, as…
Privacy-aware identification
Tatiana Komarova, Denis Nekipelov
The paper redefines econometric identification under formal privacy constraints, particularly differential privacy (DP). Traditionally, econometrics focuses on point or partial ide…
Bias-Variance Games
Yiding Feng, Ronen Gradwohl, Jason Hartline +2
Firms engaged in electronic commerce increasingly rely on predictive analytics via machine-learning algorithms to drive a wide array of managerial decisions. The tuning of many sta…
Dashboard Mechanisms for Online Marketplaces
Jason Hartline, Aleck Johnsen, Denis Nekipelov +1
This paper gives a theoretical model for design and analysis of mechanisms for online marketplaces where a bidding dashboard enables the bid-optimization of long-lived agents. We a…
Inference from Auction Prices
Jason Hartline, Aleck Johnsen, Denis Nekipelov +1
Econometric inference allows an analyst to back out the values of agents in a mechanism from the rules of the mechanism and bids of the agents. This paper gives an algorithm to sol…
Regularized Orthogonal Machine Learning for Nonlinear Semiparametric Models
Denis Nekipelov, Vira Semenova, Vasilis Syrgkanis
This paper proposes a Lasso-type estimator for a high-dimensional sparse parameter identified by a single index conditional moment restriction (CMR). In addition to this parameter,…
Mechanism Redesign
Shuchi Chawla, Jason D. Hartline, Denis Nekipelov +1
This paper develops the theory of mechanism redesign by which an auctioneer can reoptimize an auction based on bid data collected from previous iterations of the auction on bidders…
Learning and Trust in Auction Markets
Pooya Jalaly, Denis Nekipelov, Eva Tardos
In this paper, we study behavior of bidders in an experimental launch of a new advertising auction platform by Zillow, as Zillow switched from negotiated contracts to using auction…
A/B Testing of Auctions
Shuchi Chawla, Jason D. Hartline, Denis Nekipelov
For many application areas A/B testing, which partitions users of a system into an A (control) and B (treatment) group to experiment between several application designs, enables In…
Econometrics for Learning Agents
Denis Nekipelov, Vasilis Syrgkanis, Eva Tardos
The main goal of this paper is to develop a theory of inference of player valuations from observed data in the generalized second price auction without relying on the Nash equilibr…
Efficiency Guarantees from Data
Darrell Hoy, Denis Nekipelov, Vasilis Syrgkanis
Analysis of efficiency of outcomes in game theoretic settings has been a main item of study at the intersection of economics and computer science. The notion of the price of anarch…
Mechanism Design for Data Science
Shuchi Chawla, Jason Hartline, Denis Nekipelov
Good economic mechanisms depend on the preferences of participants in the mechanism. For example, the revenue-optimal auction for selling an item is parameterized by a reserve pric…