25 citations · 121 across the 26 of their papers we have counts for
11 papers · 1 filter
Consistent Submodular Maximization with Full Foresight
Eric Balkanski, Paul Dütting, Federico Fusco +4
Online algorithms with bounded recourse face three intertwined obstacles: uncertainty about the future, computational limits, and a limited budget for changes. We ask a fundamental…
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…
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…
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…
Pandora's Problem with Combinatorial Cost
Ben Berger, Tomer Ezra, Michal Feldman +1
Pandora's problem is a fundamental model in economics that studies optimal search strategies under costly inspection. In this paper we initiate the study of Pandora's problem with…
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…
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…
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,…
Prophet Inequalities for Matching with a Single Sample
Paul Dütting, Federico Fusco, Philip Lazos +2
We consider the prophet inequality problem for (not necessarily bipartite) matching problems with independent edge values, under both edge arrivals and vertex arrivals. We show con…
Submodular Maximization subject to a Knapsack Constraint: Combinatorial Algorithms with Near-optimal Adaptive Complexity
Georgios Amanatidis, Federico Fusco, Philip Lazos +3
Submodular maximization is a classic algorithmic problem with multiple applications in data mining and machine learning; there, the growing need to deal with massive instances moti…
Fast Adaptive Non-Monotone Submodular Maximization Subject to a Knapsack Constraint
Georgios Amanatidis, Federico Fusco, Philip Lazos +2
Constrained submodular maximization problems encompass a wide variety of applications, including personalized recommendation, team formation, and revenue maximization via viral mar…