P. Aguiar, E. P. Xing, M. Figueiredo, N. A. Smith, and A. Martins, An augmented lagrangian approach to constrained map inference, Proceedings of the 28th International Conference on Machine Learning (ICML-11), pp.169-176, 2011.

A. Andersson, M. Tenhunen, and F. Ygge, Integer programming for combinatorial auction winner determination, Proceedings Fourth International Conference on MultiAgent Systems, pp.39-46, 2000.
DOI : 10.1109/ICMAS.2000.858429

M. O. Ball, Heuristics based on mathematical programming. Surveys in Operations Research and Management Science, pp.21-38, 2011.

D. Bertsimas and J. Tsitsiklis, Introduction to Linear Optimization, Athena Scientific, 1997.

S. Boyd, N. Parikh, E. Chu, B. Peleato, and J. Eckstein, Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers, Foundations and Trends?? in Machine Learning, vol.3, issue.1, pp.1-122, 2011.
DOI : 10.1561/2200000016

D. Vries and R. V. Vohra, Combinatorial Auctions: A Survey, INFORMS Journal on Computing, vol.15, issue.3, pp.284-309, 2003.
DOI : 10.1287/ijoc.15.3.284.16077

J. Duchi, S. Shalev-shwartz, Y. Singer, and T. Chandra, Efficient projections onto the l 1- ball for learning in high dimensions, Proceedings of the 25th international conference on Machine learning, pp.272-279, 2008.

J. Eckstein and D. P. Bertsekas, On the Douglas???Rachford splitting method and the proximal point algorithm for maximal monotone operators, Mathematical Programming, vol.29, issue.1, pp.293-318, 1992.
DOI : 10.2140/pjm.1970.33.209

Y. Fujishima, K. Leyton-brown, and Y. Shoham, Taming the computational complexity of combinatorial auctions: Optimal and approximate approaches, International Joint Conferences on Artificial Intelligence (IJCAI), pp.548-553, 1999.

D. Gabay and B. Mercier, A dual algorithm for the solution of nonlinear variational problems via finite element approximation, Computers & Mathematics with Applications, vol.2, issue.1, pp.17-40, 1976.
DOI : 10.1016/0898-1221(76)90003-1

A. Globerson and T. S. Jaakkola, Fixing max-product: Convergent message passing algorithms for map lp-relaxations, Advances in neural information processing systems, pp.553-560, 2008.

R. Glowinski and A. Marroco, Sur l'approximation, parélémentspar´paréléments finis d'ordre un, et la résolution, par pénalisation-dualité d'une classe deprobì emes de dirichlet non linéaires, ESAIM: Mathematical Modelling and Numerical Analysis-Modélisation Mathématique et Analyse Numérique, vol.9, issue.R2, pp.41-76, 1975.

T. Hazan and A. Shashua, Norm-Product Belief Propagation: Primal-Dual Message-Passing for Approximate Inference, IEEE Transactions on Information Theory, vol.56, issue.12, pp.6294-6316, 2010.
DOI : 10.1109/TIT.2010.2079014

V. Kolmogorov, Convergent tree-reweighted message passing for energy minimization. Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol.28, issue.10, pp.1568-1583, 2006.

N. Komodakis, N. Paragios, and G. Tziritas, MRF Optimization via Dual Decomposition: Message-Passing Revisited, 2007 IEEE 11th International Conference on Computer Vision, pp.1-8, 2007.
DOI : 10.1109/ICCV.2007.4408890

URL : http://www.mas.ecp.fr/Personnel/nikos/pub/iccv07.pdf

K. Leyton-brown, E. Nudelman, and Y. Shoham, Empirical hardness models, Journal of the ACM, vol.56, issue.4, p.22, 2009.
DOI : 10.1145/1538902.1538906

K. Leyton-brown, M. Pearson, and Y. Shoham, Towards a universal test suite for combinatorial auction algorithms, Proceedings of the 2nd ACM conference on Electronic commerce , EC '00, pp.66-76, 2000.
DOI : 10.1145/352871.352879

A. F. Martins, The Geometry of Constrained Structured Prediction: Applications to Inference and Learning of Natural Language Syntax, 2012.

A. F. Martins, M. A. Figueiredo, P. M. Aguiar, N. A. Smith, and E. P. Xing, Ad 3 : Alternating directions dual decomposition for map inference in graphical models, Journal of Machine Learning Research, vol.46, 2014.

O. Miksik, V. Vineet, P. Perez, and P. H. Torr, Distributed non-convex admm-inference in large-scale random fields, British Machine Vision Conference (BMVC), 2014.

S. Parsons, J. A. Rodriguez-aguilar, and M. Klein, Auctions and bidding, ACM Computing Surveys, vol.43, issue.2, pp.1-1059, 2011.
DOI : 10.1145/1883612.1883617

S. D. Ramchurn, C. Mezzetti, A. Giovannucci, J. A. Rodriguez-aguilar, R. K. Dash et al., Trust-based mechanisms for robust and efficient task allocation in the presence of execution uncertainty, Journal of Artificial Intelligence Research, vol.35, issue.1, p.119, 2009.

S. D. Ramchurn, A. Rogers, K. Macarthur, A. Farinelli, P. Vytelingum et al., Agent-based coordination technologies in disaster management, Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems: demo papers, pp.1651-1652, 2008.

A. Roy, I. Mihailovic, and W. Zwaenepoel, X-Stream, Proceedings of the Twenty-Fourth ACM Symposium on Operating Systems Principles, SOSP '13, pp.472-488, 2013.
DOI : 10.1145/2517349.2522740

A. M. Rush, D. Sontag, M. Collins, and T. Jaakkola, On dual decomposition and linear programming relaxations for natural language processing, Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing, pp.1-11, 2010.

T. Sandholm, S. Suri, A. Gilpin, and D. Levine, Cabob: A fast optimal algorithm for combinatorial auctions, International Joint Conference on Artificial Intelligence, pp.1102-1108, 2001.

E. and S. Jr, On the generation of alternative explanations with implications for belief revision, Proceedings of the Seventh conference on Uncertainty in Artificial Intelligence, pp.339-347, 1991.

Y. Sheffi, Combinatorial Auctions in the Procurement of Transportation Services, Interfaces, vol.34, issue.4, pp.245-252, 2004.
DOI : 10.1287/inte.1040.0075

C. Sierra, R. De-lópez, M. , and D. Busquets, Multiagent Bidding Mechanisms for Robot Qualitative Navigation, Intelligent Agents VII Agent Theories Architectures and Languages, pp.198-212, 2001.
DOI : 10.1007/3-540-44631-1_14

D. Smith and J. Eisner, Dependency parsing by belief propagation, Proceedings of the Conference on Empirical Methods in Natural Language Processing, EMNLP '08, pp.145-156, 2008.
DOI : 10.3115/1613715.1613737

URL : http://dl.acm.org/ft_gateway.cfm?id=1613737&type=pdf

D. Sontag, T. Meltzer, A. Globerson, T. S. Jaakkola, and Y. Weiss, Tightening lp relaxations for map using message passing. arXiv preprint, 2012.

M. J. Wainwright, T. S. Jaakkola, and A. S. Willsky, Tree-reweighted belief propagation algorithms and approximate ml estimation by pseudo-moment matching, In Workshop on Artificial Intelligence and Statistics Society for Artificial Intelligence and Statistics Np, vol.21, p.97, 2003.

C. Yanover, T. Meltzer, and Y. Weiss, Linear programming relaxations and belief propagation ? an empirical study, J. Mach. Learn. Res, vol.7, pp.1887-1907, 2006.