Real-Time Bidding with Side Information
© 2017 Neural information processing systems foundation. All rights reserved. We consider the problem of repeated bidding in online advertising auctions when some side information (e.g. browser cookies) is available ahead of submitting a bid in the form of a d-dimensional vector. The goal for the ad...
| Main Authors: | , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
2021
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| Online Access: | https://hdl.handle.net/1721.1/137606 |
| _version_ | 1826206406069452800 |
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| author | Flajolet, Arthur Jaillet, Patrick |
| author2 | Massachusetts Institute of Technology. Operations Research Center |
| author_facet | Massachusetts Institute of Technology. Operations Research Center Flajolet, Arthur Jaillet, Patrick |
| author_sort | Flajolet, Arthur |
| collection | MIT |
| description | © 2017 Neural information processing systems foundation. All rights reserved. We consider the problem of repeated bidding in online advertising auctions when some side information (e.g. browser cookies) is available ahead of submitting a bid in the form of a d-dimensional vector. The goal for the advertiser is to maximize the total utility (e.g. the total number of clicks) derived from displaying ads given that a limited budget B is allocated for a given time horizon T. Optimizing the bids is modeled as a contextual Multi-Armed Bandit (MAB) problem with a knapsack constraint and a continuum of arms. We develop UCB-type algorithms that combine two streams of literature: the confidence-set approach to linear contextual MABs and the probabilistic bisection search method for stochastic root-finding. Under mild assumptions on the underlying unknown distribution, we establish distribution-independent regret bounds of order Õ(d · √T) when either B = ∞ or when B scales linearly with T. |
| first_indexed | 2024-09-23T13:29:17Z |
| format | Article |
| id | mit-1721.1/137606 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2024-09-23T13:29:17Z |
| publishDate | 2021 |
| record_format | dspace |
| spelling | mit-1721.1/1376062022-10-01T15:32:26Z Real-Time Bidding with Side Information Flajolet, Arthur Jaillet, Patrick Massachusetts Institute of Technology. Operations Research Center Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology. Laboratory for Information and Decision Systems © 2017 Neural information processing systems foundation. All rights reserved. We consider the problem of repeated bidding in online advertising auctions when some side information (e.g. browser cookies) is available ahead of submitting a bid in the form of a d-dimensional vector. The goal for the advertiser is to maximize the total utility (e.g. the total number of clicks) derived from displaying ads given that a limited budget B is allocated for a given time horizon T. Optimizing the bids is modeled as a contextual Multi-Armed Bandit (MAB) problem with a knapsack constraint and a continuum of arms. We develop UCB-type algorithms that combine two streams of literature: the confidence-set approach to linear contextual MABs and the probabilistic bisection search method for stochastic root-finding. Under mild assumptions on the underlying unknown distribution, we establish distribution-independent regret bounds of order Õ(d · √T) when either B = ∞ or when B scales linearly with T. 2021-11-05T19:54:14Z 2021-11-05T19:54:14Z 2017 2019-05-31T18:05:53Z Article http://purl.org/eprint/type/ConferencePaper https://hdl.handle.net/1721.1/137606 Flajolet, Arthur and Jaillet, Patrick. 2017. "Real-Time Bidding with Side Information." en Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use. application/pdf Neural Information Processing Systems (NIPS) |
| spellingShingle | Flajolet, Arthur Jaillet, Patrick Real-Time Bidding with Side Information |
| title | Real-Time Bidding with Side Information |
| title_full | Real-Time Bidding with Side Information |
| title_fullStr | Real-Time Bidding with Side Information |
| title_full_unstemmed | Real-Time Bidding with Side Information |
| title_short | Real-Time Bidding with Side Information |
| title_sort | real time bidding with side information |
| url | https://hdl.handle.net/1721.1/137606 |
| work_keys_str_mv | AT flajoletarthur realtimebiddingwithsideinformation AT jailletpatrick realtimebiddingwithsideinformation |