activity
20212026
most citedSingle-Sample Prophet Inequalities via Greedy-Ordered Selection

25 citations · 40 across the 14 of their papers we have counts for

collaborators

14 papers

cs.GT2026

Profit Maximization in Bilateral Trade against a Smooth Adversary

Simone Di Gregorio, Paul Dütting, Federico Fusco +1

Bilateral trade models the task of intermediating between two strategic agents, a seller and a buyer, who wish to trade a good. We study this problem from the perspective of a prof…

cs.GT2026

Autobidding Equilibria in Sponsored Shopping

Paul Dütting, Yuhao Li, Renato Paes Leme +2

As commerce shifts to digital marketplaces, platforms increasingly monetize traffic through Sponsored Shopping auctions. Unlike classic ``Sponsored Search", where an advertiser typ…

cs.GT2025★ 1 cited

Nearly Tight Regret Bounds for Profit Maximization in Bilateral Trade

Simone Di Gregorio, Paul Dütting, Federico Fusco +1

Bilateral trade models the task of intermediating between two strategic agents, a seller and a buyer, willing to trade a good for which they hold private valuations. We study this…

cs.DS2024

The Cost of Consistency: Submodular Maximization with Constant Recourse

Paul Dütting, Federico Fusco, Silvio Lattanzi +3

In this work, we study online submodular maximization, and how the requirement of maintaining a stable solution impacts the approximation. In particular, we seek bounds on the best…

cs.GT2024★ 2 cited

Selling Joint Ads: A Regret Minimization Perspective

Gagan Aggarwal, Ashwinkumar Badanidiyuru, Paul Dütting +1

Motivated by online retail, we consider the problem of selling one item (e.g., an ad slot) to two non-excludable buyers (say, a merchant and a brand). This problem captures, for ex…

cs.GT2024

Principal-Agent Reinforcement Learning: Orchestrating AI Agents with Contracts

Dima Ivanov, Paul Dütting, Inbal Talgam-Cohen +2

The increasing deployment of AI is shaping the future landscape of the internet, which is set to become an integrated ecosystem of AI agents. Orchestrating the interaction among AI…

cs.DS2024

Consistent Submodular Maximization

Paul Dütting, Federico Fusco, Silvio Lattanzi +2

Maximizing monotone submodular functions under cardinality constraints is a classic optimization task with several applications in data mining and machine learning. In this paper w…

cs.GT2024★ 1 cited

When Contracts Get Complex: Information-Theoretic Barriers

Paul Dütting, Michal Feldman, Yoav Gal-Tzur +1

In the combinatorial-action contract model (Dütting et al., FOCS'21) a principal delegates the execution of a complex project to an agent, who can choose any subset from a given se…

cs.LG2023

Deep Contract Design via Discontinuous Networks

Tonghan Wang, Paul Dütting, Dmitry Ivanov +2

Contract design involves a principal who establishes contractual agreements about payments for outcomes that arise from the actions of an agent. In this paper, we initiate the stud…

cs.DS2023★ 5 cited

Fully Dynamic Submodular Maximization over Matroids

Paul Dütting, Federico Fusco, Silvio Lattanzi +2

Maximizing monotone submodular functions under a matroid constraint is a classic algorithmic problem with multiple applications in data mining and machine learning. We study this c…

cs.GT2022

Approximate Optimality of Linear Contracts Under Uncertainty

Tal Alon, Paul Dütting, Yingkai Li +1

We consider a hidden-action principal-agent model, in which actions require different amounts of effort, and the agent privately knows his ability that determines his cost of effor…

cs.DS2022★ 2 cited

Deletion Robust Non-Monotone Submodular Maximization over Matroids

Paul Dütting, Federico Fusco, Silvio Lattanzi +2

Maximizing a submodular function is a fundamental task in machine learning and in this paper we study the deletion robust version of the problem under the classic matroids constrai…

cs.DS2022★ 4 cited

Deletion Robust Submodular Maximization over Matroids

Paul Dütting, Federico Fusco, Silvio Lattanzi +2

Maximizing a monotone submodular function is a fundamental task in machine learning. In this paper, we study the deletion robust version of the problem under the classic matroids c…

cs.DS2021★ 25 cited

Single-Sample Prophet Inequalities via Greedy-Ordered Selection

Constantine Caramanis, Paul Dütting, Matthew Faw +6

We study single-sample prophet inequalities (SSPIs), i.e., prophet inequalities where only a single sample from each prior distribution is available. Besides a direct, and optimal,…