activity
20192024
most citedConvergence Analysis of No-Regret Bidding Algorithms in Repeated Auctions

4 citations · 6 across the 5 of their papers we have counts for

collaborators

8 papers

cs.IR2024

Improved Online Learning Algorithms for CTR Prediction in Ad Auctions

Zhe Feng, Christopher Liaw, Zixin Zhou

In this work, we investigate the online learning problem of revenue maximization in ad auctions, where the seller needs to learn the click-through rates (CTRs) of each ad candidate…

q-fin.GN2023

Exploring the Dynamics of the Specialty Insurance Market Using a Novel Discrete Event Simulation Framework: a Lloyd's of London Case Study

Sedar Olmez, Akhil Ahmed, Keith Kam +2

This research presents a novel Discrete Event Simulation (DES) of the Lloyd's of London specialty insurance market, exploring complex market dynamics that have not been previously…

cs.AI2022

Sequential Information Design: Markov Persuasion Process and Its Efficient Reinforcement Learning

Jibang Wu, Zixuan Zhang, Zhe Feng +4

In today's economy, it becomes important for Internet platforms to consider the sequential information design problem to align its long term interest with incentives of the gig ser…

cs.GT2021

Robust Clearing Price Mechanisms for Reserve Price Optimization

Zhe Feng, Sébastien Lahaie

Setting an effective reserve price for strategic bidders in repeated auctions is a central question in online advertising. In this paper, we investigate how to set an anonymous res…

cs.GT20204 cited

Convergence Analysis of No-Regret Bidding Algorithms in Repeated Auctions

Zhe Feng, Guru Guruganesh, Christopher Liaw +2

The connection between games and no-regret algorithms has been widely studied in the literature. A fundamental result is that when all players play no-regret strategies, this produ…

cs.GT20202 cited

Reserve Price Optimization for First Price Auctions

Zhe Feng, Sébastien Lahaie, Jon Schneider +1

The display advertising industry has recently transitioned from second- to first-price auctions as its primary mechanism for ad allocation and pricing. In light of this, publishers…