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, SSPI for the basic single choice problem [Rubinstein et al., 2020], most existing SSPI results were obtained via an elegant, but inherently lossy reduction to order-oblivious secretary (OOS) policies [Azar et al., 2014]. Motivated by this discrepancy, we develop an intuitive and versatile greedy-based technique that yields SSPIs directly rather than through the reduction to OOSs. Our results can be seen as generalizing and unifying a number of existing results in the area of prophet and secretary problems. Our algorithms significantly improve on the competitive guarantees for a number of interesting scenarios (including general matching with edge arrivals, bipartite matching with vertex arrivals, and certain matroids), and capture new settings (such as budget additive combinatorial auctions). Complementing our algorithmic results, we also consider mechanism design variants. Finally, we analyze the power and limitations of different SSPI approaches by providing a partial converse to the reduction from SSPI to OOS given by Azar et al.

Single-sample prophet inequalities via greedy-ordered selection / Caramanis, Constantine; Dütting, Paul; Faw, Matthew; Fusco, Federico; Lazos, Filippos; Leonardi, Stefano; Papadigenopoulos, Orestis; Pountourakis, Emmanouil; Reiffenhäuser, Rebecca. - (2022), pp. 1298-1325. (Intervento presentato al convegno ACM/SIAM Symposium on Discrete Algorithms tenutosi a Virtuale) [10.1137/1.9781611977073.54].

Single-sample prophet inequalities via greedy-ordered selection

Fusco, Federico
;
Lazos, Filippos
;
Leonardi, Stefano
;
Papadigenopoulos, Orestis
;
Reiffenhäuser, Rebecca
2022

Abstract

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, SSPI for the basic single choice problem [Rubinstein et al., 2020], most existing SSPI results were obtained via an elegant, but inherently lossy reduction to order-oblivious secretary (OOS) policies [Azar et al., 2014]. Motivated by this discrepancy, we develop an intuitive and versatile greedy-based technique that yields SSPIs directly rather than through the reduction to OOSs. Our results can be seen as generalizing and unifying a number of existing results in the area of prophet and secretary problems. Our algorithms significantly improve on the competitive guarantees for a number of interesting scenarios (including general matching with edge arrivals, bipartite matching with vertex arrivals, and certain matroids), and capture new settings (such as budget additive combinatorial auctions). Complementing our algorithmic results, we also consider mechanism design variants. Finally, we analyze the power and limitations of different SSPI approaches by providing a partial converse to the reduction from SSPI to OOS given by Azar et al.
2022
ACM/SIAM Symposium on Discrete Algorithms
Two sided markets; single sample; combinatorial auctions
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
Single-sample prophet inequalities via greedy-ordered selection / Caramanis, Constantine; Dütting, Paul; Faw, Matthew; Fusco, Federico; Lazos, Filippos; Leonardi, Stefano; Papadigenopoulos, Orestis; Pountourakis, Emmanouil; Reiffenhäuser, Rebecca. - (2022), pp. 1298-1325. (Intervento presentato al convegno ACM/SIAM Symposium on Discrete Algorithms tenutosi a Virtuale) [10.1137/1.9781611977073.54].
File allegati a questo prodotto
File Dimensione Formato  
Caramanis_Single-Sample_2022.pdf

accesso aperto

Tipologia: Versione editoriale (versione pubblicata con il layout dell'editore)
Licenza: Creative commons
Dimensione 1.21 MB
Formato Adobe PDF
1.21 MB Adobe PDF

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1636837
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 17
  • ???jsp.display-item.citation.isi??? ND
social impact