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20172024
most citedSingle-Sample Prophet Inequalities via Greedy-Ordered Selection

25 citations · 124 across the 24 of their papers we have counts for

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Showing 2021Show all

6 papers · 1 filter

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,…

cs.GT2021★ 5 cited

Allocating Indivisible Goods to Strategic Agents: Pure Nash Equilibria and Fairness

Georgios Amanatidis, Georgios Birmpas, Federico Fusco +3

We consider the problem of fairly allocating a set of indivisible goods to a set of strategic agents with additive valuation functions. We assume no monetary transfers and, therefo…

cs.DS2021

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…

cs.GT2021★ 3 cited

On the Complexity of Equilibrium Computation in First-Price Auctions

Aris Filos-Ratsikas, Yiannis Giannakopoulos, Alexandros Hollender +2

We consider the problem of computing a (pure) Bayes-Nash equilibrium in the first-price auction with continuous value distributions and discrete bidding space. We prove that when b…

cs.GT2021★ 2 cited

RPPLNS: Pay-per-last-N-shares with a Randomised Twist

Philip Lazos, Francisco J. Marmolejo-Cossío, Xinyu Zhou +1

"Pay-per-last--shares" (PPLNS) is one of the most common payout strategies used by mining pools in Proof-of-Work (PoW) cryptocurrencies. As with any payment scheme, it is impera…

cs.DS2021

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…