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Learning algorithms for second-price auctions with reserve

https://doi.org/10.5555/2946645.3007027
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-3-642-10841-9_1openalex-snapshot
Ad Exchanges: Research Issues
inferredcites →https://doi.org/10.1007/bf01585092openalex-snapshot
Additively decomposed quasiconvex functions
inferredcites →https://doi.org/10.1007/bfb0082336openalex-snapshot
Probability in Banach Spaces
inferredcites →https://doi.org/10.1007/s00453-009-9318-zopenalex-snapshot
Maintaining Equilibria During Exploration in Sponsored Search Auctions
inferredcites →https://doi.org/10.1016/j.dss.2013.07.004openalex-snapshot
Online learning for auction mechanism in bandit setting
inferredcites →https://doi.org/10.1016/j.jcss.2007.08.002openalex-snapshot
Reducing mechanism design to algorithm design via machine learning
inferredcites →https://doi.org/10.1016/j.tcs.2004.05.012openalex-snapshot
Online learning in online auctions
inferredcites →https://doi.org/10.1023/a:1021765131316openalex-snapshot
DC Programming: Overview
inferredcites →https://doi.org/10.1109/sfcs.2003.1238232openalex-snapshot
The value of knowing a demand curve: bounds on regret for online posted-price auctions
inferredcites →https://doi.org/10.1111/j.1540-6261.1961.tb02789.xopenalex-snapshot
COUNTERSPECULATION, AUCTIONS, AND COMPETITIVE SEALED TENDERS
inferredcites →https://doi.org/10.1137/s0097539701398375openalex-snapshot
The Nonstochastic Multiarmed Bandit Problem
inferredcites →https://doi.org/10.1137/s1052623494274313openalex-snapshot
A D.C. Optimization Algorithm for Solving the Trust-Region Subproblem
inferredcites →https://doi.org/10.1145/1250910.1250918openalex-snapshot
Revenue analysis of a family of ranking rules for keyword auctions
inferredcites →https://doi.org/10.1145/1566374.1566388openalex-snapshot
The price of truthfulness for pay-per-click auctions
inferredcites →https://doi.org/10.1145/1571941.1572042openalex-snapshot
Optimizing search engine revenue in sponsored search
inferredcites →https://doi.org/10.1145/1993574.1993585openalex-snapshot
Reserve prices in internet advertising auctions
inferredcites →https://doi.org/10.1145/2020408.2020454openalex-snapshot
Bid landscape forecasting in online ad exchange marketplace
inferredcites →https://doi.org/10.1162/08997660360581958openalex-snapshot
The Concave-Convex Procedure
inferredcites →https://doi.org/10.1162/neco_a_00283openalex-snapshot
A Proof of Convergence of the Concave-Convex Procedure Using Zangwill's Theory
inferredcites →https://doi.org/10.1198/016214505000000907openalex-snapshot
Convexity, Classification, and Risk Bounds
inferredcites →https://doi.org/10.1214/aos/1015362183openalex-snapshot
Empirical Margin Distributions and Bounding the Generalization Error of Combined Classifiers
inferredcites →https://doi.org/10.1287/moor.6.1.58openalex-snapshot
Optimal Auction Design
inferredcites →https://doi.org/10.2307/1911865openalex-snapshot
A Theory of Auctions and Competitive Bidding
inferredcites →https://doi.org/10.2307/2553898openalex-snapshot
Convergence of Stochastic Processes.
inferredcites →https://doi.org/10.48550/arxiv.1210.4847openalex-snapshot
Budget Optimization for Sponsored Search: Censored Learning in MDPs
inferredcites →https://doi.org/10.48550/arxiv.1311.6838openalex-snapshot
Learning Prices for Repeated Auctions with Strategic Buyers
inferredcites →https://doi.org/10.48550/arxiv.1506.02719openalex-snapshot
Non-parametric Revenue Optimization for Generalized Second Price Auctions
inferredcites →https://doi.org/10.7551/mitpress/10290.001.0001openalex-snapshot
Foundations of Machine Learning

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.2139/ssrn.4476642openalex-extracted
Multi-Platform Budget Management in Ad Markets with Non-IC Auctions
inferred← citeshttps://doi.org/10.2139/ssrn.4823113openalex-extracted
Conformal Online Auction Design
inferred← citeshttps://doi.org/10.2139/ssrn.5014743openalex-extracted
Learning in Repeated Multi-Unit Pay-As-Bid Auctions
inferred← citeshttps://doi.org/10.1007/978-3-030-55692-1_3openalex-snapshot
Be Careful When Learning Against Adversaries: Imitative Attacker Deception in Stackelberg Security Games
inferred← citeshttps://doi.org/10.1016/j.cie.2019.106071openalex-snapshot
Optimal display-ad allocation with guaranteed contracts and supply side platforms
inferred← citeshttps://doi.org/10.1016/j.orl.2021.01.008openalex-snapshot
Maximizing revenue for publishers using header bidding and ad exchange auctions
inferred← citeshttps://doi.org/10.1109/cec.2019.8789915openalex-snapshot
A PSO-based Algorithm for Reserve Price Optimization in Online Ad Auctions
inferred← citeshttps://doi.org/10.1109/cifer.2019.8759123openalex-snapshot
Optimizing reserve prices for publishers in online ad auctions
inferred← citeshttps://doi.org/10.1109/dsaa.2016.32openalex-snapshot
Reserve Price Optimization at Scale
inferred← citeshttps://doi.org/10.1109/fuzz-ieee.2019.8858975openalex-snapshot
Fuzzy Logic based Pricing combined with Adaptive Search for Reserve Price Optimization in Online Ad Auctions
inferred← citeshttps://doi.org/10.1111/deci.12500openalex-snapshot
Adaptive Ad Network Selection for Publisher‐Return Optimization in Mobile‐App Advertising
inferred← citeshttps://doi.org/10.1145/3313276.3316331openalex-snapshot
Tight approximation ratio of anonymous pricing
inferred← citeshttps://doi.org/10.1145/3442381.3449968openalex-snapshot
Bid Prediction in Repeated Auctions with Learning
inferred← citeshttps://doi.org/10.1145/3465456.3467621openalex-snapshot
Tight Revenue Gaps among Multi-Unit Mechanisms
inferred← citeshttps://doi.org/10.1145/3630749openalex-snapshot
Optimal Auctions through Deep Learning: Advances in Differentiable Economics
inferred← citeshttps://doi.org/10.1145/3690624.3709439openalex-snapshot
Learning Adaptive Reserve Price in Display Advertising
inferred← citeshttps://doi.org/10.1287/mksc.2021.1283openalex-snapshot
Scalable Optimal Online Auctions
inferred← citeshttps://doi.org/10.1287/mksc.2022.0406openalex-snapshot
Online Causal Inference for Advertising in Real-Time Bidding Auctions
inferred← citeshttps://doi.org/10.1287/moor.2022.1313openalex-snapshot
Contextual Bandits with Cross-Learning
inferred← citeshttps://doi.org/10.1287/opre.2020.2092openalex-snapshot
Mechanism Design for Correlated Valuations: Efficient Methods for Revenue Maximization
inferred← citeshttps://doi.org/10.1609/aaai.v34i02.5600openalex-snapshot
Reinforcement Mechanism Design: With Applications to Dynamic Pricing in Sponsored Search Auctions
inferred← citeshttps://doi.org/10.21203/rs.3.rs-6765381/v1openalex-snapshot
LLM for Secure Reserve Price Optimization in Real-time Bidding
inferred← citeshttps://doi.org/10.24963/ijcai.2017/739openalex-snapshot
Reinforcement mechanism design
inferred← citeshttps://doi.org/10.4230/lipics.itcs.2023.75openalex-snapshot
Learning Reserve Prices in Second-Price Auctions
inferred← citeshttps://doi.org/10.48550/arxiv.2004.09957openalex-snapshot
Algorithms for slate bandits with non-separable reward functions
inferred← citeshttps://doi.org/10.48550/arxiv.2006.06519openalex-snapshot
Reserve Price Optimization for First Price Auctions
inferred← citeshttps://doi.org/10.48550/arxiv.2102.07454openalex-snapshot
Tight Revenue Gaps among Multi-Unit Mechanisms
inferred← citeshttps://doi.org/10.5555/3091125.3091141openalex-snapshot
Mechanism Design with Unknown Correlated Distributions: Can We Learn Optimal Mechanisms?
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