This is a collection of research and review papers of real-time bidding (RTB) based display advertising techniques. The sharing principle of these references here is for research. If any authors do not want their paper to be listed here, please feel free to contact Weinan Zhang.
You are more than welcome to update this list!
If you find a paper about RTB techniques or review which is not listed here, please
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- Display Advertising with Real-Time Bidding (RTB) and Behavioural Targeting by Jun Wang, Weinan Zhang and Shuai Yuan. ArXiv 2016.
- Learning, Prediction and Optimisation in RTB Display Advertising by Weinan Zhang and Jian Xu. CIKM 2016.
- Real-Time Bidding based Display Advertising: Mechanisms and Algorithms by Jun Wang, Shuai Yuan and Weinan Zhang. ECIR 2016.
- Real-Time Bidding: A New Frontier of Computational Advertising Research by Shuai Yuan and Jun Wang. WSDM 2015.
- Research Frontier of Real-Time Bidding based Display Advertising by Weinan Zhang. Beijing 2015.
- A Survey on Real Time Bidding Advertising by Yong Yuan. Service Operations and Logistics 2014.
- Real-time Bidding for Online Advertising: Measurement and Analysis by Shuai Yuan, Jun Wang, Xiaoxue Zhao. ADKDD 2013.
- Ad Exchanges: Research Issues by S. Muthukrishnan. Internet and network economics 2009.
- A Nonparametric Delayed Feedback Model for Conversion Rate Prediction by Yuya Yoshikawa and Yusaku Imai. ArXiv 2018.
- Robust Factorization Machines for User Response Prediction by Surabhi Punjabi and Priyanka Bhatt. WWW 2018.
- Field-weighted Factorization Machines for Click-Through Rate Prediction in Display Advertising by Junwei Pan et al. WWW 2018.
- Deep & Cross Network for Ad Click Predictions by Ruoxi Wang et al. ADKDD & TargetAd 2017.
- Ranking and Calibrating Click-Attributed Purchases in Performance Display Advertising by Sougata Chaudhuri et al. ADKDD 2017.
- A Practical Framework of Conversion Rate Prediction for Online Display Advertising by Quan Lu et al. ADKDD 2017.
- An Ensemble-Based Approach to Click-Through Rate Prediction for Promoted Listings at Etsy by Kamelia Aryafar et al. ADKDD 2017.
- Deep Interest Network for Click-Through Rate Prediction by Guorui Zhou et al. ArXiv 2017.
- DeepFM: A Factorization-Machine based Neural Network for CTR Prediction by Huifeng Guo et al. IJCAI 2017
- Learning Piece-wise Linear Models from Large Scale Data for Ad Click Prediction by Kun Gai, Xiaoqiang Zhu, Han Li, et al. Arxiv 2017.
- SEM: A Softmax-based Ensemble Model for CTR Estimation in Real-Time Bidding Advertising by Wen-Yuan Zhu et al. BigComp 2017.
- Neural Feature Embedding for User Response Prediction in Real-Time Bidding (RTB) by Enno Shioji, Masayuki Arai. ArXiv 2017.
- Field-aware Factorization Machines in a Real-world Online Advertising System by Yuchin Juan, Damien Lefortier, Olivier Chapelle. ArXiv 2017.
- Product-based Neural Networks for User Response Prediction by Yanru Qu et al. ICDM 2016.
- Sparse Factorization Machines for Click-through Rate Prediction by Zhen Pan et al. ICDM 2016.
- Deep CTR Prediction in Display Advertising by Junxuan Chen et al. MM 2016.
- Bid-aware Gradient Descent for Unbiased Learning with Censored Data in Display Advertising by Weinan Zhang, Tianxiong Zhou, Jun Wang, Jian Xu. KDD 2016.
- Large Scale CVR Prediction through Dynamic Transfer Learning of Global and Local Features by Hongxia Yang et al. BIGMINE 2016.
- Predicting ad click-through rates via feature-based fully coupled interaction tensor factorization by Lili Shan, Lei Lin, Chengjie Sun, Xiaolong Wang. Electronic Commerce Research and Applications 2016.
- Simple and Scalable Response Prediction for Display Advertising by Olivier Chapelle Criteo, Eren Manavoglu, Romer Rosales. ACM TIST 2014.
- Cost-sensitive Learning for Utility Optimization in Online Advertising Auctions by Flavian Vasile, Damien Lefortier, Olivier Chapelle. Extension under-review of the paper presented at the Workshop on E-Commerce, NIPS 2015.
- User Response Learning for Directly Optimizing Campaign Performance in Display Advertising by Kan Ren, Weinan Zhang, Yifei Rong, Haifeng Zhang, Yong Yu, Jun Wang. CIKM 2016.
- A Convolutional Click Prediction Model by Qiang Liu, Feng Yu, Shu Wu, Liang Wang. CIKM 2015.
- Factorization Machines with Follow-The-Regularized-Leader for CTR prediction in Display Advertising by Anh-Phuong Ta. BigData 2015.
- Deep Learning over Multi-field Categorical Data: A Case Study on User Response Prediction by Weinan Zhang, Tianming Du, Jun Wang. ECIR 2016.
- Offline Evaluation of Response Prediction in Online Advertising Auctions by Olivier Chapelle. WWW 2015.
- Predicting Response in Mobile Advertising with Hierarchical Importance-Aware Factorization Machine by Richard J. Oentaryo et al. WSDM 2014.
- Scalable Hierarchical Multitask Learning Algorithms for Conversion Optimization in Display Advertising by Amr Ahmed et al. WSDM 2014.
- Estimating Conversion Rate in Display Advertising from Past Performance Data by Kuang-chih Lee et al. KDD 2012.
- Scalable Hands-Free Transfer Learning for Online Advertising by Brian Dalessandro et al. KDD 2014.
- Evaluating and Optimizing Online Advertising: Forget the click, but there are good proxies by Brian Dalessandro et al. SSRN 2012.
- Modeling Delayed Feedback in Display Advertising by Olivier Chapelle. KDD 2014.
- Ad Click Prediction: a View from the Trenches by H. Brendan McMahan. KDD 2013.
- Practical Lessons from Predicting Clicks on Ads at Facebook by Xinran He et al. ADKDD 2014.
- Predicting Winning Price in Real Time Bidding with Censored Data by Wush Chi-Hsuan Wu, Mi-Yen Yeh, Ming-Syan Chen. KDD 2015.
- Handling Forecast Errors While Bidding for Display Advertising by Kevin J. Lang, Benjamin Moseley, Sergei Vassilvitskii. WWW 2012.
- Bid Landscape Forecasting in Online Ad Exchange Marketplace by Ying Cui et al. KDD 2011.
- Functional Bid Landscape Forecasting for Display Advertising by Yuchen Wang et al. ECML-PKDD 2016.
- Bidding Machine: Learning to Bid for Directly Optimizing Profits in Display Advertising by Kan Ren et al. TKDE 2018.
- Budget Constrained Bidding by Model-free Reinforcement Learning in Display Advertising by Di Wu et al. ArXiv 2018.
- Real-Time Bidding with Multi-Agent Reinforcement Learning in Display Advertising by Junqi Jin et al. ArXiv 2018.
- Deep Reinforcement Learning for Sponsored Search Real-time Bidding by Jun Zhao et al. ArXiv 2018.
- LADDER: A Human-Level Bidding Agent for Large-Scale Real-Time Online Auctions by Yu Wang et al. ArXiv 2017.
- Improving Real-Time Bidding Using a Constrained Markov Decision Process by Manxing Du et al. ADMA 2017.
- Attribution Modeling Increases Efficiency of Bidding in Display Advertising by Eustache Diemert et al. ADKDD 2017.
- Profit Maximization for Online Advertising Demand-Side Platforms by Paul Grigas et al. ArXiv 2017.
- Real-Time Bidding by Reinforcement Learning in Display Advertising by Han Cai et al. WSDM 2017.
- Managing Risk of Bidding in Display Advertising by Haifeng Zhang et al. WSDM 2017.
- Optimized Cost per Click in Taobao Display Advertising by Han Zhu et al. ArXiv 2017.
- Combining Powers of Two Predictors in Optimizing Real-Time Bidding Strategy under Constrained Budget by Chi-Chun Lin et al. CIKM 2016.
- Joint Optimization of Multiple Performance Metrics in Online Video Advertising by Sahin Cem Geyik et al. KDD 2016.
- Optimal Real-Time Bidding for Display Advertising by Weinan Zhang. PhD Thesis 2016.
- Bid-aware Gradient Descent for Unbiased Learning with Censored Data in Display Advertising by Weinan Zhang, Tianxiong Zhou, Jun Wang, Jian Xu. KDD 2016.
- Lift-Based Bidding in Ad Selection by Jian Xu et al. AAAI 2016.
- Feedback Control of Real-Time Display Advertising by Weinan Zhang et al. WSDM 2016.
- Optimal Real-Time Bidding Strategies by Joaquin Fernandez-Tapia, Olivier Guéant, Jean-Michel Lasry. ArXiv 2015.
- Programmatic Buying Bidding Strategies with Win Rate and Winning Price Estimation in Real Time Mobile Advertising by Xiang Li and Devin Guan. PAKDD 2014.
- Statistical modeling of Vickrey auctions and applications to automated bidding strategies by Joaquin Fernandez-Tapia. Working paper.
- Statistical Arbitrage Mining for Display Advertising by Weinan Zhang, Jun Wang. KDD 2015.
- Real-Time Bidding rules of thumb: analytically optimizing the programmatic buying of ad-inventory by Joaquin Fernandez-Tapia. SSRN 2015.
- Optimal Real-Time Bidding for Display Advertising by Weinan Zhang, Shuai Yuan, Jun Wang. KDD 2014.
- Bid Optimizing and Inventory Scoring in Targeted Online Advertising by Claudia Perlich et al. KDD 2012.
- Real-Time Bidding Algorithms for Performance-Based Display Ad Allocation by Ye Chen et al. KDD 2011.
- Exploring Optimal Frequency Caps in Real Time Bidding Advertising by Rui Qin et al. SocialCom 2016.
- Research on the Frequency Capping Issue in RTB Advertising：A Computational Experiment Approach by Rui Qin et al. CAC 2015.
- From 0.5 Million to 2.5 Million: Efficiently Scaling up Real-Time Bidding by Jianqian Shen et al. ICDM 2015.
- Smart Pacing for Effective Online Ad Campaign Optimization by Jian Xu et al. KDD 2015.
- An analytical solution to the budget-pacing problem in programmatic advertising by Joaquin Fernandez-Tapia. Working paper.
- Adaptive Targeting for Online Advertisement by Andrey Pepelyshev, Yuri Staroselskiy, Anatoly Zhigljavsky. Machine Learning, Optimization, and Big Data 2015.
- Real Time Bid Optimization with Smooth Budget Delivery in Online Advertising by Kuang-Chih Lee, Ali Jalali, Ali Dasdan. ADKDD 2013.
- Budget Pacing for Targeted Online Advertisements at LinkedIn by Deepak Agarwal et al. KDD 2014.
- Frequency Capping in Online Advertising by Niv Buchbinder et al. WADS 2011.
- Adaptive bidding for display advertising by Ghosh, A., Rubinstein, B. I, Vassilvitskii, S., and Zinkevich, M. 2009
- Independent Auditing of Online Display Advertising Campaigns by Patricia Callejo et al. HotNets 2016.
- Using Co-Visitation Networks For Classifying Non-Intentional Traffic by Ori Stitelman et al. Dstillery 2013.
- Impression Fraud in On-line Advertising via Pay-Per-View Networks by Kevin Springborn, Paul Barford. USENIX Security Symposium 2013.
- Understanding Fraudulent Activities in Online Ad Exchanges by Brett Stone-Grosset et al. IMC 2011.
- Optimizing the Segmentation Granularity for RTB Advertising Markets with a Two-stage Resale Model By Rui Qin et al. SMC 2016.
- Optimizing Market Segmentation Granularity in RTB Advertising: A Computational Experimental Study by Rui Qin et al. SocialCom 2016.
- Analyzing the Segmentation Granularity of RTB Advertising Markets：A Computational Experiment Approach by Rui Qin et al. SMP 2015.
- Learning Algorithms for Second-Price Auctions with Reserve by Mehryar Mohri and Andres Munoz Medina. JMLR 2016.
- Optimal Reserve Prices in Upstream Auctions: Empirical Application on Online Video Advertising by Miguel Angel Alcobendas, Sheide Chammas and Kuang-chih Lee. KDD 2016.
- Optimal Allocation of Ad Inventory in Real-Time Bidding Advertising Markets by Juanjuan Li et al. SMC 2016.
- A Dynamic Pricing Model for Unifying Programmatic Guarantee and Real-Time Bidding in Display Advertising by Bowei Chen, Shuai Yuan and Jun Wang. ADKDD 2014.
- An Empirical Study of Reserve Price Optimisation in Real-Time Bidding by Shuai Yuan et al. KDD 2014.
- Information Disclosure in Real-Time Bidding Advertising Markets by Juanjuan Li, Yong Yuan, Rui Qin. SOLI 2014.
- A Sub-linear, Massive-scale Look-alike Audience Extension System by Qiang Ma, Musen Wen, Zhen Xia, Datong Chen. KDD 2016 / PMLR 2016
- Audience Expansion for Online Social Network Advertising by Haishan Liu et al. KDD 2016.
- Implicit Look-alike Modelling in Display Ads: Transfer Collaborative Filtering to CTR by Weinan Zhang, Lingxi Chen, Jun Wang. ECIR 2016.
- Pleasing the advertising oracle: Probabilistic prediction from sampled, aggregated ground truth by Melinda Han Williams et al. ADKDD 2014.
- Focused matrix factorization for audience selection in display advertising by Kanagal B et al. ICDE 2013.
- Multi-Touch Attribution in Online Advertising with Survival Theory by Ya Zhang, Yi Wei, and Jianbiao Ren. ICDM 2014.
- Multi-Touch Attribution Based Budget Allocation in Online Advertising by Sahin Cem Geyik, Abhishek Saxena, Ali Dasdan. ADKDD 2014.
- Causally Motivated Attribution for Online Advertising. by Brian Dalessandro et al. ADKDD 2012.
- Data-driven Multi-touch Attribution Models. by Xuhui Shao, Lexin Li. KDD 2011.
- Truthfulness with Value-Maximizing Bidders: On the Limits of Approximation in Combinatorial Markets by Salman Fadaei and Martin Bichler. EJOR 2016.
- Repeated Auctions with Budgets in Ad Exchanges: Approximations and Design by Santiago R. Balseiro, Omar Besbesy, Gabriel Y. Weintraub. Management Science 2015.
- Ad Exchange: Intention Driven Auction Mechanisms for Mediating Between Publishers and Advertisers by Rina Azoulay, Esther David. WI/IAT 2015.
- Pricing Externalities in Real-Time Bidding Markets by Joseph Reisinger, Michael Driscoll. Machine Learning in Online Advertising.
- Competition between Demand-Side Intermediaries in Ad Exchanges by Lampros C. Stavrogiannis. PhD Thesis 2014.
- Auction Mechanisms for Demand-Side Intermediaries in Online Advertising Exchanges by Lampros C. Stavrogiannis, Enrico H. Gerding, Maria Polukarov. AMMAS 2014.
- Optimal Revenue-Sharing Double Auctions with Applications to Ad Exchanges by Renato Gomes, Vahab Mirrokni. WWW 2014.
- Competition and Yield Optimization in Ad Exchanges by Santiago R. Balseiro. PhD Thesis 2013.
- Selective Call Out and Real Time Bidding by Tanmoy Chakraborty. WINE 2010.
- Selling Off Privacy at Auction by Lukasz Olejnik, Tran Minh-Dung, Claude Castelluccia. NDSS 2014.
- Network Analysis of Third Party Tracking: User Exposure to Tracking Cookies through Search by Richard Gomer et al. WI 2013.
- Finding Needle in a Million Metrics: Anomaly Detection in a Large-scale Computational Advertising Platform by Bowen Zhou, Shahriar Shariat. TargetAd 2016.
- YOYI RTB datasets (with bidding information) by Kan Ren and Yifei Rong et al. CIKM 2016.
- iPinYou Global RTB Bidding Algorithm Competition Dataset by Hairen Liao et al. ADKDD 2014.
- Real-Time Bidding Benchmarking with iPinYou Dataset by Weinan Zhang et al. ArXiv 2014.
- Criteo Dataset for Product Recommendation / Counterfactual Learning by Damien Lefortier et al. What If workshop NIPS 2016.
- Criteo Conversion Logs Dataset by Criteo Labs.
- Criteo Terabyte Click Logs by Criteo Labs.
- Avazu Click Prediction by Avazu.