G. Amati and K. Van-rijsbergen, Probabilistic models of information retrieval based on measuring the divergence from randomness, ACM Transactions on Information Systems, vol.20, issue.4, 2002.
DOI : 10.1145/582415.582416

Y. Bengio, Deep Learning of Representations: Looking Forward, 2013.
DOI : 10.1007/978-3-642-39593-2_1

C. Burges, T. Shaked, E. Renshaw, A. Lazier, M. Deeds et al., Learning to rank using gradient descent, Proceedings of the 22nd international conference on Machine learning , ICML '05, pp.89-96, 2005.
DOI : 10.1145/1102351.1102363

K. W. Church and W. A. Gale, Poisson mixtures, Natural Language Engineering, vol.none, issue.02, pp.163-190, 2008.
DOI : 10.1002/asi.4630260402

S. Clinchant and E. Gaussier, Information-based models for ad hoc IR, Proceeding of the 33rd international ACM SIGIR conference on Research and development in information retrieval, SIGIR '10, p.234, 2010.
DOI : 10.1145/1835449.1835490
URL : https://hal.archives-ouvertes.fr/hal-00953830

A. Coates and A. Y. Ng, Learning Feature Representations with K-Means, Neural Networks: Tricks of the Trade, pp.561-580, 2012.
DOI : 10.1007/978-3-642-15555-0_11

R. Cummins and C. O-'riordan, Evolving local and global weighting schemes in information retrieval, Information Retrieval, vol.23, issue.1, pp.311-330, 2006.
DOI : 10.1007/s10791-006-1682-6

S. Deerwester, S. T. Dumais, G. W. Furnas, T. K. Landauer, and R. Harshman, Indexing by latent semantic analysis, Journal of the American Society for Information Science, vol.41, issue.6, pp.41391-407, 1990.
DOI : 10.1002/(SICI)1097-4571(199009)41:6<391::AID-ASI1>3.0.CO;2-9

E. Hoenkamp, Trading Spaces: On the Lore and Limitations of Latent Semantic Analysis, Advances in Information Retrieval Theory, pp.40-51
DOI : 10.1016/S0004-3702(98)00063-0

P. S. Huang, X. He, J. Gao, L. Deng, A. Acero et al., Learning deep structured semantic models for web search using clickthrough data, Proceedings of the 22nd ACM international conference on Conference on information & knowledge management, CIKM '13, 2013.
DOI : 10.1145/2505515.2505665

D. Kingma and J. Ba, Adam: A Method for Stochastic Optimization. arXiv.org, 2014.

T. Liu, Learning to Rank for Information Retrieval

Y. Lv, Y. Lv, and C. X. Zhai, Positional language models for information retrieval, Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval, SIGIR '09, p.299, 2009.
DOI : 10.1145/1571941.1571994

V. Nair and I. S. Hinton, Rectified linear units improve restricted boltzmann machines, International Conference on Machine Learning, 2010.

H. Palangi, H. Palangi, L. Deng, Y. Shen, J. Gao et al., Deep Sentence Embedding Using Long Short-Term Memory Networks: Analysis and Application to Information Retrieval, IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol.24, issue.4, 2015.
DOI : 10.1109/TASLP.2016.2520371

J. Rabin, G. Peyré, J. Delon, and M. Bernot, Wasserstein Barycenter and Its Application to Texture Mixing, SSVM, vol.6667, pp.435-446, 2011.
DOI : 10.1007/978-3-642-24785-9_37

S. E. Robertson and H. Zaragoza, The Probabilistic Relevance Framework: BM25 and Beyond, volume 3 of Foundations and Trends in Information Retrieval, 2009.

A. Schuth, F. Sietsma, S. Whiteson, and M. De-rijke, Optimizing Base Rankers Using Clicks -A Case Study Using BM25, ECIR, vol.8416, issue.7, pp.75-87, 2014.

A. Severyn and A. Moschitti, Learning to Rank Short Text Pairs with Convolutional Deep Neural Networks, Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR '15, pp.373-382
DOI : 10.1145/2766462.2767738

Y. Shen, X. He, J. Gao, L. Deng, and G. Mesnil, A Latent Semantic Model with Convolutional-Pooling Structure for Information Retrieval, Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management, CIKM '14, pp.101-110, 2014.
DOI : 10.1145/2661829.2661935

K. M. Svore and C. J. Burges, A machine learning approach for improved BM25 retrieval, Proceeding of the 18th ACM conference on Information and knowledge management, CIKM '09, 2009.
DOI : 10.1145/1645953.1646237

M. J. Taylor, H. Zaragoza, N. Craswell, S. E. Robertson, and C. Burges, Optimisation methods for ranking functions with multiple parameters, Proceedings of the 15th ACM international conference on Information and knowledge management , CIKM '06, pp.585-593, 2006.
DOI : 10.1145/1183614.1183698

C. X. Zhai, Statistical Language Models for Information Retrieval A Critical Review, Foundations and Trends?? in Information Retrieval, vol.2, issue.3, pp.137-213, 2008.
DOI : 10.1561/1500000008

L. Zhao and J. Callan, Term necessity prediction, Proceedings of the 19th ACM international conference on Information and knowledge management, CIKM '10, pp.259-268, 2010.
DOI : 10.1145/1871437.1871474
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.185.1663

G. Zheng and J. Callan, Learning to Reweight Terms with Distributed Representations, Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR '15, pp.575-584
DOI : 10.1145/2766462.2767700