Author: Deepak Agarwal
Publications
Co-authors
Productive Colleagues
- Liang Zhang
- Vanja Josifovski
- Joemon M. Jose
- 18
- 26
- 57
Publications
Chakrabarti, Deepayan, Agarwal, Deepak, Josifovski, Vanja (2008): Contextual advertising by combining relevance with click feedback. In: Proceedings of the 2008 International Conference on the World Wide Web , 2008, . pp. 417-426. https://doi.acm.org/10.1145/1367497.1367554
Agarwal, Deepak, Chen, Bee-Chung, Elango, Pradheep (2009): Spatio-temporal models for estimating click-through rate. In: Proceedings of the 2009 International Conference on the World Wide Web , 2009, . pp. 21-30. https://doi.acm.org/10.1145/1526709.1526713
Moshfeghi, Yashar, Agarwal, Deepak, Piwowarski, Benjamin, Jose, Joemon M. (2009): Movie Recommender: Semantically Enriched Unified Relevance Model for Rating Prediction in . In: Boughanem, Mohand, Berrut, Catherine, Mothe, Josiane, Soulé-Dupuy, Chantal (eds.) Advances in Information Retrieval - 31th European Conference on IR Research - ECIR 2009 April 6-9, 2009, 2009, Toulouse, France. pp. 54-65. https://dx.doi.org/10.1007/978-3-642-00958-7_8
Lu, Zhengdong, Agarwal, Deepak, Dhillon, Inderjit S. (2009): A spatio-temporal approach to collaborative filtering. In: Proceedings of the 2009 ACM Conference on Recommender Systems , 2009, . pp. 13-20. https://dx.doi.org/10.1145/1639714.1639719
Zhang, Liang, Agarwal, Deepak, Chen, Bee-Chung (2011): Generalizing matrix factorization through flexible regression priors. In: Proceedings of the 2011 ACM Conference on Recommender Systems , 2011, . pp. 13-20. https://dx.doi.org/10.1145/2043932.2043940
Agarwal, Deepak, Chen, Bee-Chung, Elango, Pradheep, Wang, Xuanhui (2012): Personalized click shaping through Lagrangian duality for online recommendation. In: Proceedings of the 35th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval , 2012, . pp. 485-494. https://dx.doi.org/10.1145/2348283.2348350
Agarwal, Deepak, Pandey, Sandeep, Josifovski, Vanja (2012): Targeting converters for new campaigns through factor models. In: Proceedings of the 2012 International Conference on the World Wide Web , 2012, . pp. 101-110. https://dx.doi.org/10.1145/2187836.2187851