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The most significant progress in recent years in online display advertising is what is known as the Real-Time Bidding (RTB) mechanism to buy and sell ads.
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Zhu, M. (2004) · 2004
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Online advertisers bidding strategies for search, experience, and credence goods: An empirical investigation
Animesh, A., Ramachandran, V., and Viswanathan, S. (2005) · 2005
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Internet advertising and the generalized second price auction: Selling billions of dollars worth of keywords
Edelman, B., Ostrovsky, M., and Schwarz, M. (2005) · 2005
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Censored data and truncated distributions
Greene, W. H. (2005) · 2005
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Logistic regression with an auxiliary data source
Liao, X., Xue, Y., and Carin, L. (2005) · 2005
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An introduction to auction theory
Menezes, F. M. and Monteiro, P. K. (2005) · 2005
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The Theory and Practice of Revenue Management
Talluri, K. T. and van Ryzin, G. J. (2005) · 2005
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Revenue maximization when bidders have budgets
Abrams, Z. (2006) · 2006
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Optimal auction design in a multi-unit environment: The case of sponsored search auctions
Edelman, B. and Schwarz, M. (2006) · 2006
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Unifying user-based and item-based collaborative filtering approaches by similarity fusion
Wang, J., De Vries, A. P., and Reinders, M. J. T. (2006) · 2006
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Just-in-time contextual advertising
Anagnostopoulos, A., Broder, A. Z., Gabrilovich, E., Josifovski, V., and Riedel, L. (2007) · 2007
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Greedy layer-wise training of deep networks
Bengio, Y., Lamblin, P., Popovici, D., Larochelle, H., et al. (2007) · 2007
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Dynamics of bid optimization in online advertisement auctions
Borgs, C., Chayes, J., Immorlica, N., Jain, K., Etesami, O., and Mahdian, M. (2007) · 2007
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A semantic approach to contextual advertising
Broder, A., Fontoura, M., Josifovski, V., and Riedel, L. (2007) · 2007
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Transferring naive bayes classifiers for text classification
Dai, W., Xue, G.-R., Yang, Q., and Yu, Y. (2007) · 2007
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Strategic bidder behavior in sponsored search auctions
Edelman, B. and Ostrovsky, M. (2007) · 2007
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Budget optimization in search-based advertising auctions
Feldman, J., Muthukrishnan, S., Pal, M., and Stein, C. (2007) · 2007
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Sponsored Search: Is Money a Motivator for Providing Relevant Results
Jansen, B. J. (2007) · 2007
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Novelty and diversity in information retrieval evaluation
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A unified architecture for natural language processing: Deep neural networks with multitask learning
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Daswani, N., Mysen, C., Rao, V., Weis, S., Gharachorloo, K., and Ghosemajumder, S. (2008) · 2008
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Position auctions with bidder-specific minimum prices
Even Dar, E., Feldman, J., Mansour, Y., and Muthukrishnan, S. (2008) · 2008
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Optimal bidding in stochastic budget constrained slot auctions
Hosanagar, K. and Cherepanov, V. (2008) · 2008
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Optimizing relevance and revenue in ad search: a query substitution approach
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Unified relevance models for rating prediction in collaborative filtering
Wang, J., De Vries, A. P., and Reinders, M. J. T. (2008) · 2008
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Zhou, Y., Chakrabarty, D., and Lukose, R. (2008) · 2008
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Agrawal, R., Gollapudi, S., Halverson, A., and Ieong, S. (2009) · 2009
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The adwords problem: online keyword matching with budgeted bidders under random permutations
Devanur, N. R. and Hayes, T. P. (2009) · 2009
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Bid optimization for broad match ad auctions
Even Dar, E., Mirrokni, V. S., Muthukrishnan, S., Mansour, Y., and Nadav, U. (2009) · 2009
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A survey of botnet and botnet detection
Feily, M., Shahrestani, A., and Ramadass, S. (2009) · 2009
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Adaptive bidding for display advertising
Ghosh, A., Rubinstein, B. I., Vassilvitskii, S., and Zinkevich, M. (2009) · 2009
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Matrix factorization techniques for recommender systems
Koren, Y., Bell, R., Volinsky, C., et al. (2009) · 2009
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Transfer learning for collaborative filtering via a rating-matrix generative model
Li, B., Yang, Q., and Xue, X. (2009) · 2009
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Learning to rank for information retrieval
Liu, T.-Y. (2009) · 2009
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Ad exchanges: Research issues
Muthukrishnan, S. (2009) · 2009
Cited alongside, same era.
Using co-visitation networks for detecting large scale online display advertising exchange fraud
Stitelman, O., Perlich, C., Dalessandro, B., Hook, R., Raeder, T., and Provost, F. (2013) · 2013
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Real-time bidding for online advertising: measurement and analysis
Yuan, S., Wang, J., and Zhao, X. (2013) · 2013
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Interactive collaborative filtering
Zhao, X., Zhang, W., and Wang, J. (2013) · 2013
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The web never forgets: Persistent tracking mechanisms in the wild
Acar, G., Eubank, C., Englehardt, S., Juarez, M., Narayanan, A., and Diaz, C. (2014) · 2014
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Budget pacing for targeted online advertisements at linkedin
Agarwal, D., Ghosh, S., Wei, K., and You, S. (2014) · 2014
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Scalable hierarchical multitask learning algorithms for conversion optimization in display advertising
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Reserve prices in internet advertising auctions: A field experiment
Ostrovsky, M. and Schwarz, M. (2009) · 2009
Cited alongside, same era.
Transfer learning for reinforcement learning domains: A survey
Taylor, M. E. and Stone, P. (2009) · 2009
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Portfolio theory of information retrieval
Wang, J. and Zhu, J. (2009) · 2009
Cited alongside, same era.
Feature hashing for large scale multitask learning
Weinberger, K., Dasgupta, A., Langford, J., Smola, A., and Attenberg, J. (2009) · 2009
Cited alongside, same era.
Optimal reserve price for the generalized second-price auction in sponsored search advertising
Xiao, B., Yang, W., and Li, J. (2009) · 2009
Cited alongside, same era.
How much can behavioral targeting help online advertising?
Yan, J., Liu, N., Wang, G., Zhang, W., Jiang, Y., and Chen, Z. (2009) · 2009
Cited alongside, same era.
Ahmed, A., Das, A., and Smola, A. J. (2014) · 2014
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Mapping the customer journey: A graph-based framework for online attribution modeling
Anderl, E., Becker, I., Wangenheim, F. V., and Schumann, J. H. (2014) · 2014
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Neural machine translation by jointly learning to align and translate
Bahdanau, D., Cho, K., and Bengio, Y. (2014) · 2014
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Modeling delayed feedback in display advertising
Chapelle, O. (2014) · 2014
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Simple and scalable response prediction for display advertising
Chapelle, O., Manavoglu, E., and Rosales, R. (2014) · 2014
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A dynamic pricing model for unifying programmatic guarantee and real-time bidding in display advertising
Chen, B., Yuan, S., and Wang, J. (2014) · 2014
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Madfraud: Investigating ad fraud in android applications
Crussell, J., Stevens, R., and Chen, H. (2014) · 2014
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Scalable hands-free transfer learning for online advertising
Dalessandro, B., Chen, D., Raeder, T., Perlich, C., Han Williams, M., and Provost, F. (2014) · 2014
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Multi-touch attribution based budget allocation in online advertising
Geyik, S. C., Saxena, A., and Dasdan, A. (2014) · 2014
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Practical lessons from predicting clicks on ads at facebook
He, X., Pan, J., Jin, O., Xu, T., Liu, B., Xu, T., Shi, Y., Atallah, A., Herbrich, R., Bowers, S., et al. (2014) · 2014
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iPinYou global rtb bidding algorithm competition dataset
Liao, H., Peng, L., Liu, Z., and Shen, X. (2014) · 2014
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Cross-domain collaborative filtering with factorization machines
Loni, B., Shi, Y., Larson, M., and Hanjalic, A. (2014) · 2014
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Estimating the incremental effects of interactions for marketing attribution
Sinha, R., Saini, S., and Anadhavelu, N. (2014) · 2014
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Path to purchase: A mutually exciting point process model for online advertising and conversion
Xu, L., Duan, J. A., and Whinston, A. (2014) · 2014
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Repeated auctions with budgets in ad exchanges: Approximations and design
Balseiro, S. R., Besbes, O., and Weintraub, G. Y. (2015) · 2015
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Optimal contracts for intermediaries in online advertising
Balseiro, S. R. and Candogan, O. (2015) · 2015
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Estimating ad impact on clicker conversions for causal attribution: A potential outcomes approach
Barajas, J., Akella, R., Flores, A., and Holtan, M. (2015) · 2015
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Online display advertising causal attribution and evaluation
Barajas Zamora, J. (2015) · 2015
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Offline evaluation of response prediction in online advertising auctions
Chapelle, O. (2015) · 2015
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A lattice framework for pricing display advertisement options with the stochastic volatility underlying model
Chen, B. and Wang, J. (2015) · 2015
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Multi-keyword multi-click advertisement option contracts for sponsored search
Chen, B., Wang, J., Cox, I. J., and Kankanhalli, M. S. (2015) · 2015
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Evaluating and optimizing online advertising: Forget the click, but there are good proxies
Dalessandro, B., Hook, R., Perlich, C., and Provost, F. (2015) · 2015
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Delving deep into rectifiers: Surpassing human-level performance on imagenet classification
He, K., Zhang, X., Ren, S., and Sun, J. (2015) · 2015
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What is an untrustworthy supply chain costing the us digital advertising industry?
Interactive Advertising Bureau (2015) · 2015
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Inside google’s secret war against ad fraud
Kantrowitz, A. (2015) · 2015
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Human-level control through deep reinforcement learning
Mnih, V., Kavukcuoglu, K., Silver, D., Rusu, A. A., Veness, J., Bellemare, M. G., Graves, A., Riedmiller, M., Fidjeland, A. K., Ostrovski, G., Petersen, S., Beattie, C., Sadik, A., Antonoglou, I., King, H., Kumaran, D., Wierstra, D., Legg, S., and Hassabis, D. (2015) · 2015
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From 0.5 million to 2.5 million: Efficiently scaling up real-time bidding
Shen, J., Orten, B., Geyik, S. C., Liu, D., Shariat, S., Bian, F., and Dasdan, A. (2015) · 2015
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Factorization machines with follow-the-regularized-leader for ctr prediction in display advertising
Ta, A.-P. (2015) · 2015
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Ad injection at scale: Assessing deceptive advertisement modifications
Thomas, K., Bursztein, E., Grier, C., Ho, G., Jagpal, N., Kapravelos, A., McCoy, D., Nappa, A., Paxson, V., Pearce, P., Provos, N., and Rajab, M. A. (2015) · 2015
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Time-weighted multi-touch attribution and channel relevance in the customer journey to online purchase
Wooff, D. A. and Anderson, J. M. (2015) · 2015
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Predicting winning price in real time bidding with censored data
Wu, W. C.-H., Yeh, M.-Y., and Chen, M.-S. (2015) · 2015
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Smart pacing for effective online ad campaign optimization
Xu, J., Lee, K.-c., Li, W., Qi, H., and Lu, Q. (2015) · 2015
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An empirical study on display ad impression viewability measurements
Zhang, W., Pan, Y., Zhou, T., and Wang, J. (2015) · 2015
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Product-based neural networks for user response prediction
Qu, Y., Cai, H., Ren, K., Zhang, W., Yu, Y., Wen, Y., and Wang, J. (2016) · 2016
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User response learning for directly optimizing campaign performance in display advertising
Ren, K., Zhang, W., Rong, Y., Zhang, H., Yu, Y., and Wang, J. (2016) · 2016
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