41 citations · 70 across the 9 of their papers we have counts for
10 papers
MIRT: Transformers for Truthful Generative Auctions with Whole-feed Permutation Externalities
Ali Elahi, Ermis Soumalias, Jason Cheuk Nam Liang +2
Modern online platforms commonly rank ads and organic content separately before blending them into a feed displayed to the user, overlooking externalities: an item's click-through…
Bayesian Uncertainty Quantification for Ranked Choice Voting Polls
Evan T. R. Rosenman, Jason Liang
Ranked choice voting (RCV) is a popular alternative voting method in which voters are asked to list their favored candidates in preference order, rather than vote for a single cand…
Online Ad Procurement in Non-stationary Autobidding Worlds
Jason Cheuk Nam Liang, Haihao Lu, Baoyu Zhou
Today's online advertisers procure digital ad impressions through interacting with autobidding platforms: advertisers convey high level procurement goals via setting levers such as…
Interpolating Item and User Fairness in Multi-Sided Recommendations
Qinyi Chen, Jason Cheuk Nam Liang, Negin Golrezaei +1
Today's online platforms heavily lean on algorithmic recommendations for bolstering user engagement and driving revenue. However, these recommendations can impact multiple stakehol…
Multi-channel Autobidding with Budget and ROI Constraints
Yuan Deng, Negin Golrezaei, Patrick Jaillet +2
In digital online advertising, advertisers procure ad impressions simultaneously on multiple platforms, or so-called channels, such as Google Ads, Meta Ads Manager, etc., each of w…
Individual Welfare Guarantees in the Autobidding World with Machine-learned Advice
Yuan Deng, Negin Golrezaei, Patrick Jaillet +2
Online advertising channels have commonly focused on maximizing total advertiser value (or welfare) to enhance long-run retention and channel healthiness. Previous literature has s…
Learning to Price against a Budget and ROI Constrained Buyer
Negin Golrezaei, Patrick Jaillet, Jason Cheuk Nam Liang +1
Internet advertisers (buyers) repeatedly procure ad impressions from ad platforms (sellers) with the aim to maximize total conversion (i.e. ad value) while respecting both budget a…
No-regret Learning in Price Competitions under Consumer Reference Effects
Negin Golrezaei, Patrick Jaillet, Jason Cheuk Nam Liang
We study long-run market stability for repeated price competitions between two firms, where consumer demand depends on firms' posted prices and consumers' price expectations called…
Decision Trees for Decision-Making under the Predict-then-Optimize Framework
Adam N. Elmachtoub, Jason Cheuk Nam Liang, Ryan McNellis
We consider the use of decision trees for decision-making problems under the predict-then-optimize framework. That is, we would like to first use a decision tree to predict unknown…
Incentive-aware Contextual Pricing with Non-parametric Market Noise
Negin Golrezaei, Patrick Jaillet, Jason Cheuk Nam Liang
We consider a dynamic pricing problem for repeated contextual second-price auctions with multiple strategic buyers who aim to maximize their long-term time discounted utility. The…