What We’re Reading, Viewing, Listening to
The iSOCRATES Reading, Viewing and Listening List
This compendium is revised regularly so don’t hesitate to stop by for your update, let others know where they can find a great, free industry resource, and join our mailing list to learn more about this and other new, free resources as they become available.
Get Our GUIDE
Download this Reading, Viewing and Listening List today to start making better informed decisions tomorrow.
To get immediate access, simply fill out the no obligation form below.
www.isocrates.com, www.charleswarner.us, www.adexchanger.com, www.exchangewire.com, www.mediapost.com, www.thedrum.com, www.digiday.com, www.adage.com, www.adweek.com, www.cmo.com, www.emarketer.com, www.warc.com, www.wsj.com/cmo, www.wsj.com/news/types/cmo, www.martech.com, www.martechadvisor.com, https://chiefmartec.com/
adexchanger, mediapost, digiday, WARC, emarketer, thedrum, marketingprofs, martechadvisor, iSOCRATES
Advertising Week (Fall), Ad:tech (Fall), Digiday (almost monthly), MediaPost (almost monthly), MarTech (Fall), dmexco (Fall), iabALM (Winter)
200MS: The Life of a Programmatic RTB Ad Impression, William Lederer for MediaCrossing, 2013 https://www.youtube.com/watch?v=rTg9l4d8MU4
Programmatic Advertising: The Successful Transformation to Automated, Data-Driven Marketing in Real-: How Time, Oliver Busch Editor, Springer, 2015; Targeted: How Technology is Revolutionizing Advertising and The Way Companies Reach Consumers, Mike Smith, Amacom, 2015; The Rise of the Platform Marketer: Performance Marketing with Google, Facebook, Twitter, Plus the Latest High-Growth Digital Advertising Platforms, Craig Dempster and John Lee, Wiley, 2015; Competing on Analytics: Updated, with a New Introduction: The New Science of Winning, Thomas H. Davenport and Jeanne Harris, Harvard Business Review Press, 2017; Digital Marketing Analytics: Making Sense of Consumer Data in a Digital World, Chuck Hemann and Ken Burbary, Que, 2013; Internet Ad Pioneers, Cory Treffiletti, Self-published, 2013; Ad Serving Technology, Gregory Cristal, Self-Published, 2014; Display Advertising with Real-Time Bidding (RTB) and Behavioural Targeting, Jun Wang, Weinan Zhang, Shuai Yuan, now Publishers, 2016; The Media Handbook, 7th Edition, Helen Katz, Routledge, 2020; AI for Marketing and Product Innovation, A.K. Pradeep, Andrew Appel, Stan Sthanunathan, Wiley, 2020; AI in Marketing Sales and Service, Peter Gentsch, Palgrave Macmillan, 2020; Hands-On Data Science for Marketing, Yoon Hyup Hwang, 2020; Introduction to Algorithmic Marketing, Ilya Katsov, 2018; Media Selling, 5th Edition, Charles Warner, William Lederer, and Brian Moroz, Wiley, 2020.
Computational Advertising Materials:
Vibhanshu Abhishek, Peter Fader, and Kartik Hosanagar. Media exposure through the funnel: A model of multi-stage attribution. Available at SSRN2158421, 2012.
Zoë Abrams. Revenue maximization when bidders have budgets. In SODA, pages 1074–1082, 2006.
Gunes Acar, Christian Eubank, Steven Englehardt, Marc Juarez, Arvind Narayanan, and Claudia Diaz. The web never forgets: Persistent tracking mechanisms in the wild. In Proceedings of the 2014 ACM SIGSAC Conference on Computer and Communications Security , pages 674–689. ACM,2014.
Deepak Agarwal, Souvik Ghosh, Kai Wei, and Siyu You. Budget pacing for targeted online advertisements at linkedin. In Proceedings of the 20th ACM SIGKDD international conference on Knowledge discovery and data mining, pages 1613–1619. ACM, 2014.
Rakesh Agrawal, Sreenivas Gollapudi, Alan Halverson, and Samuel Ieong. Diversifying search results. In Proceedings of the Second ACM International Conference on Web Search and Data Mining, pages 5–14. ACM, 2009.
Amr Ahmed, Yucheng Low, Mohamed Aly, Vanja Josifovski, and Alexander J Smola. Scalable distributed inference of dynamic user interests for behavioral targeting. In KDD, 2011.
Amr Ahmed, Abhimanyu Das, and Alexander J Smola. Scalable hierarchical multitask learning algorithms for conversion optimization in display advertising. In Proceedings of the 7th ACM international conference on Web search and data mining, pages 153–162. ACM, 2014.
Sumayah A. Alrwais, Alexandre Gerber, Christopher W. Dunn, Oliver Spatscheck, Minaxi Gupta, and Eric Osterweil. Dissecting ghost clicks: Ad fraud via misdirected human clicks. In Proceedings of the 28th Annual Computer Security Applications Conference, ACSAC ’12, pages 21–30, New York, NY, USA, 2012. ACM. ISBN 978-1-4503-1312-4. URL http://doi.acm.org/10.1145/2420950.2420954.
Kareem Amin, Michael Kearns, Peter Key, and Anton Schwaighofer. Budget optimization for sponsored search: Censored learning in mdps. In UAI, 2012.
Aris Anagnostopoulos, Andrei Z. Broder, Evgeniy Gabrilovich, Vanja Josifovski, and Lance Riedel. Just-in-time contextual advertising. In Proceedings of the Sixteenth ACM Conference on Conference on Information and Knowledge Management, CIKM ’07, pages 331–340, New York, NY, USA, 2007. ACM. ISBN 978-1-59593-803-9. URL http://doi.acm.org/10.1145/1321440.1321488.
Eva Anderl, Ingo Becker, Florian VWangenheim, and Jan Hendrik Schumann. Mapping the customer journey: A graph-based framework for online attribution modeling. Available at SSRN 2343077, 2014.
Animesh Animesh, Vandana Ramachandran, and Siva Viswanathan. Online Advertisers Bidding Strategies for Search, Experience, and Credence Goods: An Empirical Investigation. In Second Workshop on Sponsored Search Auctions. EC, 2005. URL http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.114.5347&rep=rep1&type=pdf.
Peter Auer, Nicolo Cesa-Bianchi, and Paul Fischer. Finite-time analysis of the multiarmed bandit problem. Machine learning, 47 (2-3):235–256, 2002.
Ricardo Baeza-Yates, Berthier Ribeiro-Neto, et al. Modern information retrieval, volume 463. ACM press New York, 1999.
Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio. Neural machine translation by jointly learning to align and translate. arXiv preprint arXiv:1409.0473, 2014.
Santiago Balseiro and Ozan Candogan. Optimal contracts for intermediaries in online advertising. Available at SSRN 2546609, 2015.
Santiago R Balseiro, Omar Besbes, and Gabriel Y Weintraub. Repeated auctions with budgets in ad exchanges: Approximations and design. Management Science, 61 (4):864–884, 2015. BBC. Google to charge advertisers viewed for seen ads. http://www.bbc.com/news/business-25356956, 2013. Accessed: 2016-07.
Yoshua Bengio, Pascal Lamblin, Dan Popovici, Hugo Larochelle, et al. Greedy layer-wise training of deep networks. Advances in neural information processing systems, 19:153, 2007.
Fischer Black and Myron Scholes. The pricing of options and corporate liabilities. Journal of Political Economy, 81 (3):637–654, 1973. ISSN 00223808.
Károly Boda, Ádám Máté Földes, Gábor György Gulyás, and Sándor Imre. User tracking on the web via cross-browser fingerprinting. In Nordic Conference on Secure IT Systems, pages 31–46. Springer, 2011.
Christian Borgs, Jennifer Chayes, Nicole Immorlica, Kamal Jain, Omid Etesami, and Mohammad Mahdian. Dynamics of bid optimization in online advertisement auctions. In Proceedings of the 16th international conference on World Wide Web, pages 531–540. ACM, 2007.
Leo Breiman. Bagging predictors. Machine learning, 24 (2):123–140, 1996.
Leo Breiman. Random forests. Machine learning, 45 (1):5–32, 2001.
Leo Breiman, Jerome Friedman, Charles J Stone, and Richard A Olshen. Classification and regression trees. CRC press, 1984.
Andrei Broder, Marcus Fontoura, Vanja Josifovski, and Lance Riedel. A semantic approach to contextual advertising. In Proceedings of the 30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR ’07, pages 559–566, New York, NY, USA, 2007. ACM. ISBN 978-1-59593-597-7. URL http://doi.acm.org/10.1145/1277741.1277837.
Andrei Broder, Evgeniy Gabrilovich, Vanja Josifovski, George Mavromatis, and Alex Smola. Bid generation for advanced match in sponsored search. In WSDM, pages 515–524. ACM, 2011. Interactive Advertising Bureau. What is an untrustworthy supply chain costing the us digital advertising industry? 2015.
Nicolo Cesa-Bianchi, Claudio Gentile, and Yishay Mansour. Regret minimization for reserve prices in second-price auctions. In Proceedings of the Twenty-Fourth Annual ACM-SIAM Symposium on Discrete Algorithms, pages 1190–1204. Society for Industrial and Applied Mathematics, 2013.
Tanmoy Chakraborty, Eyal Even-Dar, Sudipto Guha, Yishay Mansour, and S Muthukrishnan. Selective call out and real time bidding. In Internet and Network Economics, pages 145–157. 2010.
Olivier Chapelle. Modeling delayed feedback in display advertising. In Proceedings of the 20th ACM SIGKDD international conference on Knowledge discovery and data mining, pages 1097–1105. ACM, 2014.
Olivier Chapelle. Offline evaluation of response prediction in online advertising auctions. WWW, 2015.
Olivier Chapelle, Eren Manavoglu, and Romer Rosales. Simple and scalable response prediction for display advertising. ACM Transactions on Intelligent Systems and Technology (TIST) , 5 (4):61, 2014.
Bowei Chen and Jun Wang. A lattice framework for pricing display ad options with the stochastic volatility underlying model. arXiv preprint arXiv:1409.0697, 2014.
Bowei Chen, Jun Wang, Ingemar J Cox, and Mohan S Kankanhalli. Multikeyword multi-click option contracts for sponsored search advertising. CoRR , 2013.
Bowei Chen, Shuai Yuan, and Jun Wang. A dynamic pricing model for unifying programmatic guarantee and real-time bidding in display advertising. In Proceedings of the Eighth International Workshop on Data Mining for Online Advertising, ADKDD’14, pages 1:1–1:9, New York, NY, USA, 2014. ACM. ISBN 978-1-4503-2999-6. URL http://doi.acm.org/10.1145/2648584.2648585.
Tianqi Chen, Zhao Zheng, Qiuxia Lu, Weinan Zhang, and Yong Yu. Featurebased matrix factorization. arXiv preprint arXiv:1109.2271, 2011a.
Ye Chen, Pavel Berkhin, Bo Anderson, and Nikhil R Devanur. Real-time bidding algorithms for performance-based display ad allocation. In Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining, pages 1307–1315. ACM, 2011b.
Charles LA Clarke, Maheedhar Kolla, Gordon V Cormack, Olga Vechtomova, Azin Ashkan, Stefan Büttcher, and Ian MacKinnon. Novelty and diversityin information retrieval evaluation. In Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval, pages 659–666. ACM, 2008.
Ronan Collobert and Jason Weston. A unified architecture for natural language processing: Deep neural networks with multitask learning. In Proceedings of the 25th international conference on Machine learning, pages 160–167. ACM, 2008.
Jonathan Crussell, Ryan Stevens, and Hao Chen. Madfraud: Investigating ad fraud in android applications. In Proceedings of the 12th annual international conference on Mobile systems, applications, and services, pages 123–134. ACM, 2014.
Ying Cui, Ruofei Zhang, Wei Li, and Jianchang Mao. Bid landscape forecasting in online ad exchange marketplace. In KDD, pages 265–273. ACM, 2011.
Dorota M Dabrowska. Non-parametric regression with censored survival time data. Scandinavian Journal of Statistics, pages 181–197, 1987.
Wenyuan Dai, Gui-Rong Xue, Qiang Yang, and Yong Yu. Transferring naïve bayes classifiers for text classification. In AAAI, 2007.
Brian Dalessandro, Rod Hook, Claudia Perlich, and Foster Provost. Evaluating and optimizing online advertising: Forget the click, but there are good proxies. 2012a.
Brian Dalessandro, Claudia Perlich, Ori Stitelman, and Foster Provost. Causally motivated attribution for online advertising. In Proceedings of the Sixth International Workshop on Data Mining for Online Advertising and Internet Economy, page 7. ACM, 2012b.
Brian Dalessandro, Daizhuo Chen, Troy Raeder, Claudia Perlich, Melinda Han Williams, and Foster Provost. Scalable hands-free transfer learning for online advertising. In Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD ’14, pages 1573–1582, New York, NY, USA, 2014a. ACM. ISBN 978-1-4503-2956-9. URL http://doi.acm.org/10.1145/2623330.2623349.
Brian Dalessandro, Daizhuo Chen, Troy Raeder, Claudia Perlich, Melinda Han Williams, and Foster Provost. Scalable hands-free feature learning for online advertising. In KDD, 2014b.
Neil Daswani, Chris Mysen, Vinay Rao, Stephen Weis, Kourosh Gharachorloo, and Shuman Ghosemajumder. Online advertising fraud. Crimeware: understanding new attacks and defenses, 40 (2):1–28, 2008.
Li Deng, Xiaodong He, and Jianfeng Gao. Deep stacking networks for information retrieval. In 2013 IEEE International Conference on Acoustics, Speech and Signal Processing, pages 3153–3157. IEEE, 2013.
Nikhil R Devenur and Thomas P Hayes. The adwords problem: online keyword matching with budgeted bidders under random permutations. In EC, pages 71–78. ACM, 2009.
Josh Dreller. A brief history of paid search advertising. http://searchengineland.com/a-brief-history-of-paid-search-advertising-33792 (last visited 13/12/2011), 2010.
Michael Durbin. All about high-frequency trading. McGraw Hill Professional, 2010.
Peter Eckersley. How unique is your web browser? In International Symposium on Privacy Enhancing Technologies Symposium, pages 1–18. Springer, 2010.
Benjamin Edelman and Michael Schwarz. Optimal auction design in a multi-unit environment: The case of sponsored search auctions. Unpublished manuscript, Harvard Business School, 2006. URL http://scholar.google.com/scholar?hl=en&btnG=Search&q=intitle:Optimal+Auction+Design+in+a+Multi-unit+Environment+:+The+Case+of+Sponsored+Search+Auctions#0.
Benjamin Edelman, Michael Ostrovsky, and Michael Schwarz. Internet advertising and the generalized second price auction: Selling billions of dollars worth of keywords. Technical report, National Bureau of Economic Research, 2005.
Eyal Even-Dar, Jon Feldman, Yishay Mansour, and S. Muthukrishnan. Position auctions with bidder-specific minimum prices. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 5385 LNCS:577–584, 2008. ISSN 03029743.
Eyal Even Dar, Vahab S Mirrokni, S Muthukrishnan, Yishay Mansour, and Uri Nadav. Bid optimization for broad match ad auctions. In WWW, pages 231–240. ACM, 2009.
Maryam Feily, Alireza Shahrestani, and Sureswaran Ramadass. A survey of botnet and botnet detection. In 2009 Third International Conference on Emerging Security Information, Systems and Technologies, pages 268–273. IEEE, 2009.
Jon Feldman, S Muthukrishnan, Martin Pal, and Cliff Stein. Budget optimization in search-based advertising auctions. In EC, 2007.
Jerome Friedman, Trevor Hastie, and Robert Tibshirani. The elements of statistical learning, volume 1. Springer series in statistics Springer, Berlin, 2001.
Jerome H Friedman. Greedy function approximation: a gradient boosting machine. Annals of statistics, pages 1189–1232, 2001.
Jerome H Friedman. Stochastic gradient boosting. Computational Statistics & Data Analysis, 38 (4):367–378, 2002.
Gian M Fulgoni. Fraud in digital advertising: A multibillion-dollar black hole. Journal of Advertising Research, pages JAR–2016, 2016.
Sahin Cem Geyik, Abhishek Saxena, and Ali Dasdan. Multi-touch attribution based budget allocation in online advertising. In Proceedings of 20th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, pages 1–9. ACM, 2014.
Arpita Ghosh, Benjamin I P Rubinstein, Sergei Vassilvitskii, and Martin Zinkevich. Adaptive bidding for display advertising. In WWW , 2009. ISBN 9781605584874.
Richard Gomer, Eduarda Mendes Rodrigues, Natasa Milic-Frayling, and MC Schraefel. Network analysis of third party tracking: User exposure to tracking cookies through search. In Web Intelligence (WI) and Intelligent Agent Technologies (IAT), 2013 IEEE/WIC/ACM International Joint Conferences on, volume 1, pages 549–556. IEEE, 2013. Google. Ad traffic quality resource center. http://www.google.com/ads/adtrafficquality/index.html. Last visited on 04/07/2016.
Jagadeesh Gorla, Neal Lathia, Stephen Robertson, and Jun Wang. Probabilistic group recommendation via information matching. In Proceedings of the 22nd international conference on World Wide Web, pages 495–504. ACM, 2013.
JY Gorla. A bi-directional unified Model for information retrieval . PhD thesis, UCL (University College London), 2016.
Thore Graepel, Joaquin Q Candela, Thomas Borchert, and Ralf Herbrich. Web-scale bayesian click-through rate prediction for sponsored search advertising in microsoft’s bing search engine. In Proceedings of the 27th International Conference on Machine Learning (ICML-10) , pages 13–20, 2010.
Rob Graham. A brief history of digital ad buying and selling. http://www.clickz.com/clickz/column/1721924/a-brief-history-digital-ad-buying-selling ((last visited 13/12/2011), 2010).
William H Greene. Censored data and truncated distributions. Available at SSRN 825845, 2005.
R Gummadi, PB Key, and A Proutiere. Optimal bidding strategies in dynamic auctions with budget constraints. In CCC, pages 588–588. IEEE, 2011.
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun. Delving deep into rectifiers: Surpassing human-level performance on imagenet classification. In Proceedings of the IEEE International Conference on Computer Vision, pages 1026–1034, 2015.
Xinran He, Junfeng Pan, Ou Jin, Tianbing Xu, Bo Liu, Tao Xu, Yanxin Shi, Antoine Atallah, Ralf Herbrich, Stuart Bowers, et al. Practical lessons from predicting clicks on ads at facebook. In Proceedings of the Eighth International Workshop on Data Mining for Online Advertising, pages 1–9. ACM, 2014.
Geoffrey Hinton, Li Deng, Dong Yu, George E Dahl, Abdel-rahman Mohamed, Navdeep Jaitly, Andrew Senior, Vincent Vanhoucke, Patrick Nguyen, Tara N Sainath, et al. Deep neural networks for acoustic modeling in speech recognition: The shared views of four research groups. IEEE Signal Processing Magazine, 29(6):82–97, 2012.
Kartik Hosanagar and Vadim Cherepanov. Optimal bidding in stochastic budget constrained slot auctions. In EC, 2008.
Bernard J. Jansen. Sponsored Search: Is Money a Motivator for Providing Relevant Results. IEEE Computer, 2007.
Thorsten Joachims. Optimizing search engines using clickthrough data. In Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining, pages 133–142. ACM, 2002.
Norman L Johnson. Survival models and data analysis, volume 74. John Wiley & Sons, 1999.
K Sparck Jones, Steve Walker, and Stephen E. Robertson. A probabilistic model of information retrieval: development and comparative experiments: Part 2. Information Processing & Management, 36(6):809–840, 2000.
Yuchin Juan, Yong Zhuang, Wei-Sheng Chin, and Chih-Jen Lin. Field-aware factorization machines for ctr prediction. 2016.
Ren Kan,Weinan Zhang, Yifei Rong, Haifeng Zhang, Yong Yu, and JunWang. User response learning for directly optimizing campaign performance in display advertising. In Proceedings of the ACM international conference on Conference on information & knowledge management. ACM, 2016.
Alex Kantrowitz. Inside google’s secret war against ad fraud. Ad Age, May 2015.
Edward L Kaplan and Paul Meier. Nonparametric estimation from incomplete observations. Journal of the American statistical association, 53 (282):457–481, 1958.
Niklas Karlsson and Jianlong Zhang. Applications of feedback control in online advertising. In American Control Conference (ACC), 2013, pages 6008–6013. IEEE, 2013.
Scott Karp. Google adwords: A brief history of online advertising innovation. http://publishing2.com/2008/05/ 27/google-adwords-a-brief-history-of-online-advertising-innovation/(last visited 13/12/2011), 2008.
Bill Kee. Attribution playbook – google analytics. http://services.google.com/fh/files/misc/attribution_playbook.pdf, 2012. Accessed: 09-Jun-2016.
David Kenny and John F. Marshall. Contextual marketing: The real business of the internet. http://hbswk.hbs. edu/archive/2124.html (last visited 13/12/2011), 2001.
Brendan Kitts and Benjamin Leblanc. Optimal bidding on keyword auctions. Electronic Markets, 14 (3):186–201, 2004.
Robert Kleinberg and Tom Leighton. The value of knowing a demand curve: Bounds on regret for online posted-price auctions. In Foundations of Computer Science, 2003. Proceedings. 44th Annual IEEE Symposium on pages 594–605. IEEE, 2003.
Yehuda Koren, Robert Bell, Chris Volinsky, et al. Matrix factorization techniques for recommender systems. Computer, 42 (8):30–37, 2009.
Kevin J Lang, Benjamin Moseley, and Sergei Vassilvitskii. Handling forecast errors while bidding for display advertising. In Proceedings of the 21st international conference on World Wide Web, pages 371–380. ACM, 2012.
Yann LeCun and Yoshua Bengio. Convolutional networks for images, speech, and time series. The handbook of brain theory and neural networks, 3361 (10):1995, 1995.
Yann LeCun, Léon Bottou, Yoshua Bengio, and Patrick Haffner. Gradient-based learning applied to document recognition. Proceedings of the IEEE, 86 (11):2278–2324, 1998.
Kuang-chih Lee, Burkay Orten, Ali Dasdan, and Wentong Li. Estimating conversion rate in display advertising from past erformance data. In Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining, pages 768–776. ACM, 2012.
Kuang-Chih Lee, Ali Jalali, and Ali Dasdan. Real time bid optimization with smooth budget delivery in online advertising. ADKDD, 2013a. URL http://dl.acm.org/citation.cfm?doid=2501040.2501979.
Kuang-Chih Lee, Ali Jalali, and Ali Dasdan. Real time bid optimization with smooth budget delivery in online advertising. In Proceedings of the Seventh International Workshop on Data Mining for Online Advertising, page 1. ACM, 2013b.
Bin Li, Qiang Yang, and Xiangyang Xue. Transfer learning for collaborative filtering via a rating-matrix generative model. In ICML, pages 617–624. ACM, 2009.
Hang Li and Zhengdong Lu. Deep learning for information retrieval. SIGIR tutorial , 2016.
Hairen Liao, Lingxiao Peng, Zhenchuan Liu, and Xuehua Shen. iPinYou global rtb bidding algorithm competition dataset. In Proceedings of the Eighth International Workshop on Data Mining for Online Advertising, pages 1–6. ACM, 2014.
Xuejun Liao, Ya Xue, and Lawrence Carin. Logistic regression with an auxiliary data source. In ICML, pages 505–512. ACM, 2005.
Tie-Yan Liu. Learning to rank for information retrieval. Foundations and Trends in Information Retrieval, 3 (3):225–331, 2009.
Babak Loni, Yue Shi, Martha Larson, and Alan Hanjalic. Cross-domain collaborative filtering with factorization machines. In European Conference on Information Retrieval, pages 656–661. Springer, 2014.
Ashish Mangalampalli, Adwait Ratnaparkhi, Andrew O Hatch, Abraham Bagherjeiran, Rajesh Parekh, and Vikram Pudi. A feature-pair-based associative classification approach to look-alike modeling for conversion oriented user-targeting in tail campaigns. In WWW, pages 85–86. ACM, 2011.
Steven Matthews. A Technical Primer on Auction Theory I: Independent Private Values. Number 1096. 1995.
R Preston McAfee. The design of advertising exchanges. Review of Industrial Organization, 39 (3):169–185, 2011.
H Brendan McMahan, Gary Holt, David Sculley, Michael Young, Dietmar Ebner, Julian Grady, Lan Nie, Todd Phillips, Eugene Davydov, Daniel Golovin, et al. Ad click prediction: a view from the trenches. In Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining, pages 1222–1230. ACM, 2013.
Aranyak Mehta, Amin Saberi, Umesh V Vazirani, and Vijay V Vazirani. Ad-Words and Generalized On-line Matching. In FOCS, 2005.
Aranyak Mehta, Amin Saberi, Umesh Vazirani, and Vijay Vazirani. Adwords and generalized online matching. Journal of the ACM (JACM), 54 (5):22, 2007.
Aditya Krishna Menon, Krishna-Prasad Chitrapura, Sachin Garg, Deepak Agarwal, and Nagaraj Kota. Response prediction using collaborative filtering with hierarchies and side-information. In Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining, pages 141–149. ACM, 2011.
Paul Robert Milgrom. Putting auction theory to work. Cambridge University Press, 2004.
Volodymyr Mnih, Koray Kavukcuoglu, David Silver, Andrei A Rusu, Joel Veness, Marc G Bellemare, Alex Graves, Martin Riedmiller, Andreas K Fidjeland, Georg Ostrovski, et al. Human-level control through deep reinforcement learning. Nature, 518 (7540):529–533, 2015.
S Muthukrishnan. Ad exchanges: Research issues. In Internet and network economics, pages 1–12. Springer, 2009.
S Muthukrishnan, Martin Pál, and Zoya Svitkina. Stochastic models for budget optimization in search-based advertising. In Internet and Network Economics. 2007.
R. B. Myerson. Optimal auction design. Mathematics of Operations Research, 6 (1):58–73, 1981. ISSN 0364-765X.
Moni Naor and Benny Pinkas. Secure accounting and auditing on the web. Computer Networks and ISDN Systems, 30 (1):541–550, 1998.
Richard J Oentaryo, Ee-Peng Lim, Jia-Wei Low, David Lo, and Michael Finegold. Predicting response in mobile advertising with hierarchical importance-aware factorization machine. In Proceedings of the 7th ACM international conference on Web search and data mining, pages 123–132. ACM, 2014a.
Richard Jayadi Oentaryo, Ee-Peng Lim, Michael Finegold, David Lo, Feida Zhu, Clifton Phua, Eng-Yeow Cheu, Ghim-Eng Yap, Kelvin Sim, Minh Nhut Nguyen, et al. Detecting click fraud in online advertising: a data mining approach. Journal of Machine Learning Research, 15 (1):99–140, 2014b.
Martin Osborne. A course in game theory, volume 29. 1995. ISBN 0262650401.
Michael Ostrovsky and Michael Schwarz. Reserve prices in internet advertising auctions: A field experiment. Search, pages 1–18, 2009. ISSN 15565068.
Sinno Jialin Pan and Qiang Yang. A survey on transfer learning. Knowledge and Data Engineering, IEEE Transactions on, 22 (10):1345–1359, 2010.
Claudia Perlich, Brian Dalessandro, Rod Hook, Ori Stitelman, Troy Raeder, and Foster Provost. Bid optimizing and inventory scoring in targeted online advertising. In KDD, pages 804–812, 2012.
Jay M Ponte and W Bruce Croft. A language modeling approach to information retrieval. In Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval, pages 275–281. ACM, 1998.
Filip Radlinski, Andrei Broder, Peter Ciccolo, Evgeniy Gabrilovich, Vanja Josifovski, and Lance Riedel. Optimizing relevance and revenue in ad search. In SIGIR, pages 403–410, 2008.
Troy Raeder, Ori Stitelman, Brian Dalessandro, Claudia Perlich, and Foster Provost. Design principles of massive, robust prediction systems. In Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD ’12, pages 1357–1365, New York, NY, USA, 2012. ACM. ISBN 978-1-4503-1462-6. URL http://doi.acm.org/10.1145/2339530.2339740.
Steffen Rendle. Factorization machines. In Data Mining (ICDM), 2010 IEEE 10th International Conference on, pages 995–1000. IEEE, 2010.
Steffen Rendle. Factorization machines with libfm. ACM Transactions on Intelligent Systems and Technology (TIST), 3 (3):57, 2012.
Steffen Rendle and Lars Schmidt-Thieme. Pairwise interaction tensor factorization for personalized tag recommendation. In Proceedings of the third ACM international conference on Web search and data mining, pages 81–90. ACM, 2010.
Steffen Rendle, Zeno Gantner, Christoph Freudenthaler, and Lars Schmidt-Thieme. Fast context-aware recommendations with factorization machines. In Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval, pages 635–644. ACM, 2011.
Stephen E Robertson. The probability ranking principle in ir. Journal of Documentation, 33 (4):294–304, 1977.
Stephen E Robertson, ME Maron, and William S Cooper. The unified probabilistic model for ir. In International Conference on Research and Development in Information Retrieval, pages 108–117. Springer, 1982. Paul Samuelson. Rational theory of warrant pricing. Industrial Management Review, 6:13–31, 1965.
Xuhui Shao and Lexin Li. Data-driven multi-touch attribution models. In Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD ’11, pages 258–264, New York, NY, USA, 2011. ACM. ISBN 978-1-4503-0813-7. URL http://doi.acm.org/10.1145/2020408.2020453.
Lloyd S Shapley. A value for n-person games. Technical report, DTIC Document, 1952.
Jianqiang Shen, Burkay Orten, Sahin Cem Geyik, Daniel Liu, Shahriar Shariat, Fang Bian, and Ali Dasdan. From 0.5 million to 2.5 million: Efficiently scaling up real-time bidding. In ICDM, 2015.
Ritwik Sinha, Shiv Saini, and N Anadhavelu. Estimating the incremental effects of interactions for marketing attribution. In Behavior, Economic and Social Computing (BESC), 2014 International Conference on , pages 1–6. IEEE, 2014.
Arnold WM Smeulders, Marcel Worring, Simone Santini, Amarnath Gupta, and Ramesh Jain. Content-based image retrieval at the end of the early years. IEEE Transactions on pattern analysis and machine intelligence, 22 (12):1349–1380, 2000.
Ashkan Soltani, Shannon Canty, Quentin Mayo, Lauren Thomas, and Chris Jay Hoofnagle. Flash cookies and privacy. In AAAI spring symposium: intelligent information privacy management, volume 2010, pages 158–163, 2010.
Kevin Springborn and Paul Barford. Impression fraud in on-line advertising via pay-per-view networks. In USENIX Security, pages 211–226, 2013.
Ori Stitelman, Claudia Perlich, Brian Dalessandro, Rod Hook, Troy Raeder, and Foster Provost. Using co-visitation networks for detecting large scale online display advertising exchange fraud. In Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining, pages 1240–1248. ACM, 2013.
Brett Stone-Gross, Ryan Stevens, Apostolis Zarras, Richard Kemmerer, Chris Kruegel, and Giovanni Vigna. Understanding fraudulent activities in online ad exchanges. In Proceedings of the 2011 ACM SIGCOMM conference on Internet measurement conference, pages 279–294. ACM, 2011.
Anh-Phuong Ta. Factorization machines with follow-the-regularized-leader for ctr prediction in display advertising. In Big Data (Big Data), 2015 IEEE International Conference on , pages 2889–2891. IEEE, 2015.
Kalyan T. Talluri and Garrett J. van Ryzin. The Theory and Practice of Revenue Management. Springer, 2005.
Matthew E. Taylor and Peter Stone. Transfer learning for reinforcement learning domains: A survey. J. Mach. Learn. Res, 10:1633–1685, December 2009. ISSN 1532-4435. The Washington Post. Google ends its dispute with yahoo. http://www.washingtonpost.com/wp-dyn/articles/A52880-2004Aug9.html (last visited 02/06/2012), 2004.
Kurt Thomas, Elie Bursztein, Chris Grier, Grant Ho, Nav Jagpal, Alexandros Kapravelos, Damon McCoy, Antonio Nappa, Vern Paxson, Paul Pearce, et al. Ad injection at scale: Assessing deceptive advertisement modifications. In 2015 IEEE Symposium on Security and Privacy, pages 151–167. IEEE, 2015.
Stephen Tyree, Kilian Q. Weinberger, Kunal Agrawal, and Jennifer Paykin. Parallel boosted regression trees for web search ranking. In Proceedings of the 20th International Conference on World Wide Web, WWW ’11, pages 387–396, New York, NY, USA, 2011. ACM. ISBN 978-1-4503-0632-4. URL http://doi.acm.org/10.1145/1963405.1963461.
Nevena Vratonjic, Mohammad Hossein Manshaei, Maxim Raya, and Jean-Pierre Hubaux. Isps and ad networks against botnet ad fraud. In International Conference on Decision and Game Theory for Security, pages 149–167. Springer, 2010.
Jun Wang and Bowei Chen. Selling futures online advertising slots via option contracts. In Proceedings of the 21st International Conference on World Wide Web, pages 627–628. ACM, 2012.
Jun Wang and Jianhan Zhu. Portfolio theory of information retrieval. In Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval, pages 115–122. ACM, 2009.
Jun Wang, Arjen P De Vries, and Marcel JT Reinders. Unifying user-based and item-based collaborative filtering approaches by similarity fusion. In SIGIR, 2006.
Jun Wang, Arjen P De Vries, and Marcel JT Reinders. Unified relevance models for rating prediction in collaborative filtering. ACM Transactions on Information Systems (TOIS) , 26 (3):16, 2008.
Kilian Weinberger, Anirban Dasgupta, John Langford, Alex Smola, and Josh Attenberg. Feature hashing for large scale multitask learning. In Proceedings of the 26th Annual International Conference on Machine Learning, pages 1113–1120. ACM, 2009.
David A Wooff and Jillian M Anderson. Time-weighted multi-touch attribution and channel relevance in the customer journey to online purchase.Journal of Statistical Theory and Practice, (ahead-of-print):1–23, 2014.
Wush Chi-Hsuan Wu, Mi-Yen Yeh, and Ming-Syan Chen. Predicting winning price in real time bidding with censored data. In Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining , pages 1305–1314. ACM, 2015.
Baichun Xiao, W Yang, and J Li. Optimal reserve price for the generalized second-price auction in sponsored search advertising. Journal of Electronic Commerce Research, 10 (3):114–129, 2009. ISSN 1526-6133. URL http://www.csulb.edu/journals/jecr/issues/20093/Paper1.pdf.
Jian Xu, Kuang-chih Lee, Wentong Li, Hang Qi, and Quan Lu. Smart pacing for effective online ad campaign optimization. In Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining , pages 2217–2226. ACM, 2015.
Jian Xu, Xuhui Shao, Jianjie Ma, Kuang-chih Lee, Hang Qi, and Quan Lu. Lift-based bidding in ad selection. In Proceedings of the 30th AAAI Conference on Artificial Intelligence, 2016.
Lizhen Xu, Jason A Duan, and Andrew Whinston. Path to purchase: A mutually exciting point process model for online advertising and conversion. Management Science, 60 (6):1392–1412, 2014.
Jun Yan, Ning Liu, Gang Wang, and Wen Zhang. How much can behavioral targeting help online advertising? Proceeding WWW ’09 Proceedings of the 18th international conference on World wide web, pages 261–270, 2009a. ISSN 08963207. URL http://portal.acm.org/citation.cfm?id=1526745.
Jun Yan, Ning Liu, Gang Wang, Wen Zhang, Yun Jiang, and Zheng Chen. How much can behavioral targeting help online advertising? In WWW, pages 261–270. ACM, 2009b.
Shuai Yuan, Ahmad Zainal Abidin, Marc Sloan, and Jun Wang. Internet advertising: An interplay among advertisers, online publishers, ad exchanges and web users. arXiv preprint arXiv:1206.1754, 2012.
Shuai Yuan, Jun Wang, and Xiaoxue Zhao. Real-time bidding for online advertising: Measurement and analysis. In Proceedings of the Seventh International Workshop on Data Mining for Online Advertising , ADKDD ’13, pages 3:1–3:8, New York, NY, USA, 2013a. ACM. ISBN 978-1-4503-2323-9. URL http://doi.acm.org/10.1145/2501040.2501980.
Shuai Yuan, Jun Wang, and Xiaoxue Zhao. Real-time bidding for online advertising: measurement and analysis. In ADKDD, 2013b.
Shuai Yuan, Bowei Chen, Jun Wang, Peter Mason, and Sam Seljan. An Empirical Study of Reserve Price Optimisation in Real-Time Bidding. In KDD, 2014.
Weinan Zhang and Jun Wang. Statistical arbitrage mining for display advertising. In Proceedings of the 21st ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD’15, 2015.
Weinan Zhang, Ying Zhang, Bin Gao, Yong Yu, Xiaojie Yuan, and Tie-Yan Liu. Joint optimization of bid and budget allocation in sponsored search. In KDD, pages 1177–1185. ACM, 2012.
Weinan Zhang, Shuai Yuan, and Jun Wang. Optimal real-time bidding for display advertising. In Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD ’14, pages 1077–1086, New York, NY, USA, 2014a. ACM. ISBN 978-1-4503-2956-9. URL http://doi.acm.org/10.1145/2623330.2623633.
Weinan Zhang, Ye Pan, Zhou Tianxiong, and Jun Wang. An empirical study on display ad impression viewability measurements, 2015.
Weinan Zhang, Lingxi Chen, and Jun Wang. Implicit look-alike modelling in display ads: Transfer collaborative filtering to ctr estimation. In European Conference on Information Retrieval, pages 589–601. Springer, 2016a.
Weinan Zhang, Tianming Du, and Jun Wang. Deep learning over multi-field categorical data. In European Conference on Information Retrieval, pages 45–57. Springer, 2016b.
Weinan Zhang, Kan Ren, and Jun Wang. Optimal real-time bidding frameworks discussion. arXiv preprint arXiv:1602.01007, 2016c.
Weinan Zhang, Yifei Rong, JunWang, Tianchi Zhu, and XiaofanWang. Feedback control of real-time display advertising. In Proceedings of the 9th ACM International Conference on Web Search and Data Mining. ACM, 2016d.
Weinan Zhang, Tianxiong Zhou, Jun Wang, and Jian Xu. Bid-aware gradient descent for unbiased learning with censored data in display advertising. In Proceedings of the 22nd ACM SIGKDD international conference on Knowledge discovery and data mining. ACM, 2016e.
Ya Zhang, Yi Wei, and Jianbiao Ren. Multi-touch attribution in online advertising with survival theory. In Data Mining (ICDM), 2014 IEEE International Conference, pages 687–696. IEEE, 2014b.
Ying Zhang, Weinan Zhang, Bin Gao, Xiaojie Yuan, and Tie-Yan Liu. Bid keyword suggestion in sponsored search based on competitiveness and relevance. IPM, 2014c.
Yuyu Zhang, Hanjun Dai, Chang Xu, Jun Feng, Taifeng Wang, Jiang Bian, BinWang, and Tie-Yan Liu. Sequential click prediction for sponsored search with recurrent neural networks. arXiv preprint arXiv:1404.5772, 2014d.
Xiaoxue Zhao, Weinan Zhang, and Jun Wang. Interactive collaborative filtering. In Proceedings of the 22nd ACM international conference on Conference on information & knowledge management, pages 1411–1420. ACM, 2013.
Yunhong Zhou, Deeparnab Chakrabarty, and Rajan Lukose. Budget constrained bidding in keyword auctions and online knapsack problems. In Internet and Network Economics, pages 566–576. 2008.
Mu Zhu. Recall, precision and average precision. Department of Statistics and Actuarial Science, University of Waterloo, Waterloo, 2, 2004.
Yunzhang Zhu, Gang Wang, Junli Yang, Dakan Wang, Jun Yan, Jian Hu, and Zheng Chen. Optimizing Search Engine Revenue in Sponsored Search. In SIGIR, 2009.
How can we partner to create value for you?