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Creative plays a great important role in e-commerce for exhibiting products.
Mushroom records drawn from the audubon society field guide to north american mushrooms
Jeff Schlimmer. 1981 · 1981
Earlier work this paper cites.
Eligibility traces for off-policy policy evaluation
Doina Precup. 2000 · 2000
Earlier work this paper cites.
Finite-time Analysis of the Multiarmed Bandit Problem
Peter Auer, Nicolò Cesa-Bianchi, and Paul Fischer. 2002 · 2002
Earlier work this paper cites.
Learning to rank using gradient descent. In Machine Learning, Proceedings of the Twenty-Second International Conference (ICML 2005), Bonn, Germany, August 7-11, 2005 (ACM International Conference Proceeding Series, Vol. 119) , Luc De Raedt and Stefan Wrobel (Eds.). ACM, 89–96
Christopher J. C. Burges, Tal Shaked, Erin Renshaw, Ari Lazier, Matt Deeds, Nicole Hamilton, and Gregory N. Hullender. 2005 · 2005
Earlier work this paper cites.
Learning to rank: from pairwise approach to listwise approach. In Machine Learning, Proceedings of the Twenty-Fourth International Conference (ICML 2007), Corvallis, Oregon, USA, June 20-24, 2007 (ACM International Conference Proceeding Series, Vol. 227) , Zoubin Ghahramani (Ed.). ACM, 129–136
Zhe Cao, Tao Qin, Tie-Yan Liu, Ming-Feng Tsai, and Hang Li. 2007 · 2007
Earlier work this paper cites.
ImageNet: A large-scale hierarchical image database. In 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2009), 20-25 June 2009, Miami, Florida, USA . IEEE Computer Society, 248–255
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Fei-Fei Li. 2009 · 2009
Earlier work this paper cites.
A contextual-bandit approach to personalized news article recommendation. In Proceedings of the 19th International Conference on World Wide Web, WWW 2010, Raleigh, North Carolina, USA, April 26-30, 2010 , Michael Rappa, Paul Jones, Juliana Freire, and Soumen Chakrabarti (Eds.). ACM, 661–670
Lihong Li, Wei Chu, John Langford, and Robert E. Schapire. 2010 · 2010
Earlier work this paper cites.
Click-through rate estimation for rare events in online advertising
Xuerui Wang, Wei Li, Ying Cui, Ruofei Zhang, and Jianchang Mao. 2011 · 2011
Earlier work this paper cites.
The impact of visual appearance on user response in online display advertising. In Proceedings of the 21st World Wide Web Conference, WWW 2012, Lyon, France, April 16-20, 2012 (Companion Volume) , Alain Mille, Fabien L. Gandon, Jacques Misselis, Michael Rabinovich, and Steffen Staab (Eds.). ACM, 457–458
Javad Azimi, Ruofei Zhang, Yang Zhou, Vidhya Navalpakkam, Jianchang Mao, and Xiaoli Z. Fern. 2012 · 2012
Earlier work this paper cites.
Multimedia features for click prediction of new ads in display advertising. In The 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD , Qiang Yang, Deepak Agarwal, and Jian Pei (Eds.). ACM, 777–785
Haibin Cheng, Roelof van Zwol, Javad Azimi, Eren Manavoglu, Ruofei Zhang, Yang Zhou, and Vidhya Navalpakkam. 2012 · 2012
Earlier work this paper cites.
Thompson Sampling for Contextual Bandits with Linear Payoffs. In Proceedings of the 30th International Conference on Machine Learning, ICML 2013, Atlanta, GA, USA, 16-21 June 2013 (JMLR Workshop and Conference Proceedings, Vol. 28) . JMLR.org, 127–135
Shipra Agrawal and Navin Goyal. 2013 · 2013
Earlier work this paper cites.
Learning to Optimize via Posterior Sampling
Daniel Russo and Benjamin Van Roy. 2014 · 2014
Earlier work this paper cites.
Image Feature Learning for Cold Start Problem in Display Advertising. In Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, IJCAI 2015, Buenos Aires, Argentina, July 25-31, 2015 , Qiang Yang and Michael J. Wooldridge (Eds.). AAAI Press, 3728–3734
Kaixiang Mo, Bo Liu, Lei Xiao, Yong Li, and Jie Jiang. 2015 · 2015
Cited alongside, same era.
Karen Simonyan and Andrew Zisserman. 2015 · 2015
Cited alongside, same era.
Deep CTR Prediction in Display Advertising. In Proceedings of the 2016 ACM Conference on Multimedia Conference, MM 2016, Amsterdam, The Netherlands, October 15-19, 2016 , Alan Hanjalic, Cees Snoek, Marcel Worring, Dick C. A. Bulterman, Benoit Huet, Aisling Kelliher, Yiannis Kompatsiaris, and Jin Li (Eds.). ACM, 811–820
Junxuan Chen, Baigui Sun, Hao Li, Hongtao Lu, and Xian-Sheng Hua. 2016 · 2016
Cited alongside, same era.
An Introduction to Deep Reinforcement Learning
Vincent François-Lavet, Peter Henderson, Riashat Islam, Marc G. Bellemare, and Joelle Pineau. 2018 · 2018
Later among the works it cites.
Deep Bayesian Bandits Showdown: An Empirical Comparison of Bayesian Deep Networks for Thompson Sampling. In 6th International Conference on Learning Representations, ICLR 2018, Vancouver, BC, Canada, April 30 - May 3, 2018, Conference Track Proceedings . OpenReview.net
Carlos Riquelme, George Tucker, and Jasper Snoek. 2018 · 2018
Later among the works it cites.
Telepath: Understanding users from a human vision perspective in large-scale recommender systems. In Thirty-Second AAAI Conference on Artificial Intelligence
Yu Wang, Jixing Xu, Aohan Wu, Mantian Li, Yang He, Jinghe Hu, and Weipeng P Yan. 2018 · 2018
Later among the works it cites.
Aesthetic-based Clothing Recommendation. In Proceedings of the 2018 World Wide Web Conference on World Wide Web, WWW 2018, Lyon, France, April 23-27, 2018 , Pierre-Antoine Champin, Fabien L. Gandon, Mounia Lalmas, and Panagiotis G. Ipeirotis (Eds.). ACM, 649–658
Wenhui Yu, Huidi Zhang, Xiangnan He, Xu Chen, Li Xiong, and Zheng Qin. 2018 · 2018
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Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning. In Proceedings of the 33nd International Conference on Machine Learning, ICML 2016, New York City, NY, USA, June 19-24, 2016 (JMLR Workshop and Conference Proceedings, Vol. 48) , Maria-Florina Balcan and Kilian Q. Weinberger (Eds.). JMLR.org, 1050–1059
Yarin Gal and Zoubin Ghahramani. 2016 · 2016
Cited alongside, same era.
Deep residual learning for image recognition. In Proceedings of the IEEE conference on computer vision and pattern recognition . 770–778
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun. 2016 · 2016
Cited alongside, same era.
Photo Aesthetics Ranking Network with Attributes and Content Adaptation. In Computer Vision - ECCV 2016 - 14th European Conference, Amsterdam, The Netherlands, October 11-14, 2016, Proceedings, Part I (Lecture Notes in Computer Science, Vol. 9905) , Bastian Leibe, Jiri Matas, Nicu Sebe, and Max Welling (Eds.). Springer, 662–679
Shu Kong, Xiaohui Shen, Zhe L. Lin, Radomír Mech, and Charless C. Fowlkes. 2016 · 2016
Cited alongside, same era.
A Computational Approach to Relative Aesthetics
Parag S. Chandakkar, Vijetha Gattupalli, and Baoxin Li. 2017 · 2017
Cited alongside, same era.
Bandit Algorithms in Interactive Information Retrieval. In Proceedings of the ACM SIGIR International Conference on Theory of Information Retrieval, ICTIR 2017, Amsterdam, The Netherlands, October 1-4, 2017 , Jaap Kamps, Evangelos Kanoulas, Maarten de Rijke, Hui Fang, and Emine Yilmaz (Eds.). ACM, 327–328
Dorota Glowacka. 2017 · 2017
Cited alongside, same era.
Automatic differentiation in pytorch
Adam Paszke, Sam Gross, Soumith Chintala, Gregory Chanan, Edward Yang, Zachary DeVito, Zeming Lin, Alban Desmaison, Luca Antiga, and Adam Lerer. 2017 · 2017
Cited alongside, same era.
Customer acquisition via display advertising using multi-armed bandit experiments
Eric M Schwartz, Eric T Bradlow, and Peter S Fader. 2017 · 2017
Cited alongside, same era.
NIMA: Neural Image Assessment
Hossein Talebi Esfandarani and Peyman Milanfar. 2018 · 2018
Cited alongside, same era.
Later among the works it cites.
Combining Text and Image data for Product Recommendability Modeling. In 2019 IEEE International Conference on Big Data (Big Data), Los Angeles, CA, USA, December 9-12, 2019 . IEEE, 5992–5994
Mark Capelo, Karan Aggarwal, and Pranjul Yadav. 2019 · 2019
Later among the works it cites.
Bandit algorithms in recommender systems. In Proceedings of the 13th ACM Conference on Recommender Systems . 574–575
Dorota Glowacka. 2019 · 2019
Later among the works it cites.
What You Look Matters?: Offline Evaluation of Advertising Creatives for Cold-start Problem. In Proceedings of the 28th ACM International Conference on Information and Knowledge Management, CIKM 2019, Beijing, China, November 3-7, 2019 , Wenwu Zhu, Dacheng Tao, Xueqi Cheng, Peng Cui, Elke A. Rundensteiner, David Carmel, Qi He, and Jeffrey Xu Yu (Eds.). ACM, 2605–2613
Zhichen Zhao, Lei Li, Bowen Zhang, Meng Wang, Yuning Jiang, Li Xu, Fengkun Wang, and Wei-Ying Ma. 2019 · 2019
Later among the works it cites.
Category-Specific CNN for Visual-aware CTR Prediction at JD. com. In Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining . 2686–2696
Hu Liu, Jing Lu, Hao Yang, Xiwei Zhao, Sulong Xu, Hao Peng, Zehua Zhang, Wenjie Niu, Xiaokun Zhu, Yongjun Bao, et al · 2020
Later among the works it cites.
Hierarchical Adaptive Contextual Bandits for Resource Constraint based Recommendation. In Proceedings of The Web Conference 2020 . 292–302
Mengyue Yang, Qingyang Li, Zhiwei Qin, and Jieping Ye. 2020 · 2020
Later among the works it cites.
Will people like your image? learning the aesthetic space. In 2018 IEEE Winter Conference on Applications of Computer Vision (WACV) . IEEE, 2048–2057
Katharina Schwarz, Patrick Wieschollek, and Hendrik PA Lensch. 2018 · 2057
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