ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2103.10246
  4. Cited By
Stochastic Bandits for Multi-platform Budget Optimization in Online
  Advertising
v1v2 (latest)

Stochastic Bandits for Multi-platform Budget Optimization in Online Advertising

16 March 2021
Vashist Avadhanula
Riccardo Colini-Baldeschi
S. Leonardi
Karthik Abinav Sankararaman
Okke Schrijvers
ArXiv (abs)PDFHTML

Papers citing "Stochastic Bandits for Multi-platform Budget Optimization in Online Advertising"

13 / 13 papers shown
Title
Bandits with Anytime Knapsacks
Bandits with Anytime Knapsacks
Eray Can Elumar
Cem Tekin
Osman Yagan
138
0
0
30 Jan 2025
Online Joint Bid/Daily Budget Optimization of Internet Advertising
  Campaigns
Online Joint Bid/Daily Budget Optimization of Internet Advertising Campaigns
Alessandro Nuara
F. Trovò
N. Gatti
Marcello Restelli
56
31
0
03 Mar 2020
Introduction to Multi-Armed Bandits
Introduction to Multi-Armed Bandits
Aleksandrs Slivkins
625
1,010
0
15 Apr 2019
Online Learning for Measuring Incentive Compatibility in Ad Auctions
Online Learning for Measuring Incentive Compatibility in Ad Auctions
Zhe Feng
Okke Schrijvers
Eric Sodomka
38
22
0
21 Jan 2019
Adversarial Bandits with Knapsacks
Adversarial Bandits with Knapsacks
Nicole Immorlica
Karthik Abinav Sankararaman
Robert Schapire
Aleksandrs Slivkins
144
115
0
28 Nov 2018
Learning to Bid Without Knowing your Value
Learning to Bid Without Knowing your Value
Zhe Feng
Chara Podimata
Vasilis Syrgkanis
58
57
0
03 Nov 2017
Combinatorial Semi-Bandits with Knapsacks
Combinatorial Semi-Bandits with Knapsacks
Karthik Abinav Sankararaman
Aleksandrs Slivkins
72
50
0
23 May 2017
Linear Contextual Bandits with Knapsacks
Linear Contextual Bandits with Knapsacks
Shipra Agrawal
Nikhil R. Devanur
159
143
0
24 Jul 2015
An efficient algorithm for contextual bandits with knapsacks, and an
  extension to concave objectives
An efficient algorithm for contextual bandits with knapsacks, and an extension to concave objectives
Shipra Agrawal
Nikhil R. Devanur
Lihong Li
88
91
0
10 Jun 2015
Resourceful Contextual Bandits
Resourceful Contextual Bandits
Ashwinkumar Badanidiyuru
John Langford
Aleksandrs Slivkins
94
120
0
27 Feb 2014
Bandits with concave rewards and convex knapsacks
Bandits with concave rewards and convex knapsacks
Shipra Agrawal
Nikhil R. Devanur
133
200
0
24 Feb 2014
Bandits with Knapsacks
Bandits with Knapsacks
Ashwinkumar Badanidiyuru
Robert D. Kleinberg
Aleksandrs Slivkins
104
432
0
11 May 2013
Knapsack based Optimal Policies for Budget-Limited Multi-Armed Bandits
Knapsack based Optimal Policies for Budget-Limited Multi-Armed Bandits
Long Tran-Thanh
Archie C. Chapman
A. Rogers
N. Jennings
100
193
0
09 Apr 2012
1