Statistical predictor identification, Annals of the Institute of Statistical Mathematics, vol.3, issue.1, pp.203-217, 1970. ,
DOI : 10.1007/BF02506337
Neural network learning : Theoretical Foundations, 1999. ,
DOI : 10.1017/CBO9780511624216
Graphical Models -Methods for data analysis and Mining, 2002. ,
The Convergence of a Class of Double-rank Minimization Algorithms, IMA Journal of Applied Mathematics, vol.6, issue.3, pp.222-231, 1970. ,
DOI : 10.1093/imamat/6.3.222
« A limited memory algorithm for bound constrained optimization, J. Sci. Comput, vol.16, issue.5, pp.1190-1208, 1995. ,
« An algorithm for bayesian network construction from data, 6th International Workshop on Artificial Intelligence and Statistics, pp.83-90, 1997. ,
Learning belief networks from data, Proceedings of the sixth international conference on Information and knowledge management , CIKM '97, pp.325-331, 1997. ,
DOI : 10.1145/266714.266920
Learning Bayesian networks from data: An information-theory based approach, Artificial Intelligence, vol.137, issue.1-2, pp.43-90, 2002. ,
DOI : 10.1016/S0004-3702(02)00191-1
Transformational Characterization of Equivalent Bayesian Network Structures, Proceedings of the 11th Annual Conference on Uncertainty in Artificial Intelligence (UAI-95), pp.87-98, 1995. ,
Learning equivalence classes of bayesian-network structures, J. Mach. Learn. Res, vol.2, pp.445-498, 2002. ,
« Optimal structure identification with greedy search, Journal of Machine Learning Research, vol.3, pp.507-554, 2002. ,
« Efficient Approximations for the Marginal Likelihood of Bayesian Networks with Hidden Variables, Machine Learning, vol.29, issue.2/3, pp.181-212, 1997. ,
DOI : 10.1023/A:1007469629108
A Bayesian method for the induction of probabilistic networks from data, Machine Learning, pp.309-347, 1992. ,
DOI : 10.1007/BF00994110
A new approach to variable metric algorithms, The Computer Journal, vol.13, issue.3, pp.317-322, 1970. ,
DOI : 10.1093/comjnl/13.3.317
A family of variable-metric methods derived by variational means, Mathematics of Computation, vol.24, issue.109, pp.23-26, 1970. ,
DOI : 10.1090/S0025-5718-1970-0258249-6
« A Survey of Algorithms for Real-Time Bayesian Network Inference, 2002. ,
Bayesian networks : The combination of knowledge and statistical data, Proceedings of the 10th Conference on Uncertainty in Artificial Intelligence, 1994. ,
« -entropy and -capacity of sets in functional spaces », Amer, Math. Soc. Translations, vol.17, pp.277-364, 1961. ,
Factor graphs and the sum-product algorithm, IEEE Transactions on Information Theory, vol.47, issue.2, pp.498-519, 2001. ,
DOI : 10.1109/18.910572
« Local computations with probabilities on graphical structures and their applications to expert systems, J. Royal Statistical Society B, vol.50, pp.157-224, 1988. ,
An Object-Oriented Class Library for Nonlinear Optimization, 1994. ,
DOI : 10.2172/10136172
Modeling by shortest data description, Automatica, vol.14, issue.5, pp.465-471, 1978. ,
DOI : 10.1016/0005-1098(78)90005-5
« The Bayesian Choice : a decision theoric motivation, 1994. ,
DOI : 10.1007/978-1-4757-4314-2
Estimating the dimension of a model », The annals of Statistics, pp.461-464, 1978. ,
Conditioning of quasi-Newton methods for function minimization, Mathematics of Computation, vol.24, issue.111, pp.647-656, 1970. ,
DOI : 10.1090/S0025-5718-1970-0274029-X
« Low-discrepancy Sets for High-Dimensional Rectangles: A Survey, Bulletin of the European Association for Theoretical Computer Science, vol.70, pp.67-76, 2000. ,
The Nature of Statistical Learning Theory, 1995. ,
« On the uniform convergence of relative frequencies of events to their probabilities », Theory of probability and its applications, pp.264-280, 1971. ,
Theory of Learning and Generalization, 1997. ,
Required sample size for learning sparse bayesian networks with many variables », LANL e-print cs, 2002. ,
a limited memory FORTRAN code for solving bound constrained optimization problems, 1994. ,