7 papers
One Model, Two Markets: Bid-Aware Generative Recommendation
Yanchen Jiang, Zhe Feng, Christopher P. Mah +2
Generative Recommender Systems using semantic ids, such as TIGER (Rajput et al., 2023), have emerged as a widely adopted competitive paradigm in sequential recommendation. However,…
The Average-Value Allocation Problem
Kshipra Bhawalkar, Zhe Feng, Anupam Gupta +3
We initiate the study of centralized algorithms for welfare-maximizing allocation of goods to buyers subject to average-value constraints. We show that this problem is NP-hard to a…
Position Auctions in AI-Generated Content
Santiago Balseiro, Kshipra Bhawalkar, Yuan Deng +7
We consider an extension to the classic position auctions in which sponsored creatives can be added within AI generated content rather than shown in predefined slots. New challenge…
Online Bidding under RoS Constraints without Knowing the Value
Sushant Vijayan, Zhe Feng, Swati Padmanabhan +3
We consider the problem of bidding in online advertising, where an advertiser aims to maximize value while adhering to budget and Return-on-Spend (RoS) constraints. Unlike prior wo…
Auto-bidding and Auctions in Online Advertising: A Survey
Gagan Aggarwal, Ashwinkumar Badanidiyuru, Santiago R. Balseiro +23
In this survey, we summarize recent developments in research fueled by the growing adoption of automated bidding strategies in online advertising. We explore the challenges and opp…
Deep Reinforcement Learning for Sequential Combinatorial Auctions
Sai Srivatsa Ravindranath, Zhe Feng, Di Wang +3
Revenue-optimal auction design is a challenging problem with significant theoretical and practical implications. Sequential auction mechanisms, known for their simplicity and stron…