Overall Objectives
Scientific Foundations
Application Domains
New Results
Other Grants and Activities


Major publications by the team in recent years

E. Althaus, A. Caprara, H.-P. Lenhof, K. Reinert.
Multiple sequence alignment with arbitrary gap costs: Computing an optimal solution using polyhedral combinatorics., in: Proc. European Conference on Computational Biology, Bioinformatics, October 2002, vol. 18, no Supplement 2, p. S4–S16.
E. Althaus, K. Mehlhorn.
Traveling Salesman-Based Curve Reconstruction in Polynomial Time, in: SIAM Journal on Computing, 2001, vol. 31, no 1, p. 27–66.
E. Balas, A. Bockmayr, N. Pisaruk, L. Wolsey.
On unions and dominants of polytopes, in: Mathematical Programming, Ser. A, 2004, vol. 299, p. 223-239.
A. Bockmayr, A. Courtois.
Using hybrid concurrent constraint programming to model dynamic biological systems, in: 18th International Conference on Logic Programming, ICLP'02, Copenhagen, Springer, LNCS 2401, 2002, p. 85-99.
A. Bockmayr, J. N. Hooker.
Constraint Programming, in: 12: Discrete Optimization, K. Aardal, G. Nemhauser, R. Weismantel (editors), Handbooks in Operations Research and Management Science, Elsevier, 2005, chap. 10, p. 559–600.
A. Bockmayr, V. Weispfenning.
Solving numerical constraints, in: Handbook of Automated Reasoning, A. Robinson, A. Voronkov (editors), Elsevier, 2001, vol. 1, chap. 12, p. 751-842.
Y. Guermeur, A. Elisseeff, D. Zelus.
Bound on the risk for M-SVMs, in: Statistical Learning, Theory and Applications, 2002, p. 48–52.
Y. Guermeur, C. Geourjon, P. Gallinari, G. Deléage.
Improved performance in protein secondary structure prediction by inhomogeneous score combination, in: Bioinformatics, 1999, vol. 15, no 5, p. 413–421.
Y. Guermeur.
Combining discriminant models with new multi-class SVMs, in: Pattern Analysis and Applications, 2002, vol. 5, no 2, p. 168–179.
Y. Guermeur, A. Lifchitz, R. Vert.
A kernel for protein secondary structure prediction, in: Kernel Methods in Computational Biology, B. Schölkopf, K. Tsuda, J.-P. Vert (editors), The MIT Press, 2004, p. 193–206.
Y. Guermeur, H. Paugam-Moisy.
Théorie de l'apprentissage de Vapnik et SVM, Support Vector Machines, in: Apprentissage Automatique, M. Sebban, G. Venturini (editors), Hermès, 1999, p. 109–138.
V. Y. Lunin, A. Urzhumtsev, A. Bockmayr.
Direct phasing by binary integer programming, in: Acta Crystallographica Section A, 2002, vol. 58, p. 283-291.
P. Musé, F. Sur, F. Cao, Y. Gousseau, J.-M. Morel.
An a contrario decision method for shape element recognition, Technical report, CMLA, ENS Cachan, 2004, no 2004-16.

Publications of the year

Articles in refereed journals and book chapters

E. Althaus, A. Caprara, H.-P. Lenhof, K. Reinert.
Aligning Multiple sequences by Cutting Planes, in: Mathematical Programming, to appear.
E. Althaus, S. Funke, S. Har-Peled, J. Könemann, E. A. Ramos, M. Skutella.
Approximating k-hop minimum-spanning trees, in: Operations Research Letters, March 2005, vol. 33, no 2, p. 115–120.
F. Denis, R. Gilleron, F. Letouzey.
Learning From Positive and Unlabeled Examples, in: Theoretical Computer Science, 2005, vol. 348, p. 70-83.
P. Dupont, F. Denis, Y. Esposito.
Links between Probabilistic Automata and Hidden Markov Models: probability distributions, learning models and induction algorithms, in: Pattern Recognition: Special Issue on Grammatical Inference Techniques & Applications, 2005, vol. 38/9, p. 1349-1371.
Y. Guermeur, A. Elisseeff, D. Zelus.
A comparative study of multi-class support vector machines in the unifying framework of large margin classifiers, in: Applied Stochastic Models in Business and Industry, 2005, vol. 21, no 2, p. 199–214.
Y. Guermeur, O. Teytaud.
Estimation et contrôle des performances en généralisation des réseaux de neurones, in: Apprentissage Connexionniste, Y. Bennani (editor), to appear, Hermès, 2005.
P. Musé, F. Sur, F. Cao, Y. Gousseau, J.-M. Morel.
An a contrario decision method for shape element recognition, in: International Journal of Computer Vision, to appear, 2006.
P. Musé, F. Sur, F. Cao, Y. Gousseau, J.-M. Morel.
Shape recognition based on an a contrario methodology, in: Statistics and analysis of shapes, H. Krim, A. Yezzi (editors), Birkhauser, 2006.

Publications in Conferences and Workshops

E. Althaus, R. Naujoks.
Computing Steiner Minimum Trees in Hamming Metric, in: Proceedings of the 17th Annual ACM-SIAM Symposium on Discrete Algorithms (SODA-06), Miami, USA, to appear, 2006.
C. Capponi, G. Fichant, Y. Quentin, F. Denis.
Boosting Blast, in: Applied Stochastic Models and Data Analysis ASMDA 2005, Brest, France, 2005.
C. Capponi, G. Fichant, Y. Quentin, F. Denis.
Boosting BLAST for classifying protein domains, in: Actes de JOBIM 2005, Lyon, France, 2005.
F. Denis, Y. Esposito.
Learning classes of Probabilistic Automata, in: COLT 2004, LNAI, 2004, no 3120, p. 124-139.
F. Denis, Y. Esposito.
Rational stochastic languages, in: TAGI 2005, 2005.
Y. Guermeur, M. Maumy, F. Sur.
Model selection for multi-class SVMs, in: ASMDA'05, Brest, France, 2005, p. 507–516.
C. Magnan.
Apprentissage semi-supervisé asymétrique et estimations d'affinités locales dans les protéines, in: Actes de CAP 05, F. Denis (editor), PUG, 2005, p. 297-312.
N. Sapay, Y. Guermeur, G. Deléage.
Prediction of in-plane amphipathic membrane segments based on an SVM method, in: JOBIM'05, Lyon, France, 2005, p. 299–311.

Internal Reports

F. Cao, J. Delon, A. Desolneux, P. Musé, F. Sur.
A unified framework for detecting groups and application to shape recognition, (submitted to a journal), INRIA, 2005, no RR-5695
Y. Darcy, Y. Guermeur.
Radius-margin bound on the leave-one-out error of multi-class SVMs, Technical report, INRIA, 2005, no RR-5780

References in notes

C. Burges.
A tutorial on support vector machines for pattern recognition, in: Data Mining and Knowledge Discovery, June 1998, vol. 2, no 2, p. 121–167.
B. Carl, I. Stephani.
Entropy, compactness, and the approximation of operators, Cambridge University Press, Cambridge, UK, 1990.
W. J. Cook, W. H. Cunningham, W. R. Pulleyblank, A. Schrijver.
Combinatorial Optimization, Wiley, 1998.
C. Cortes, V. Vapnik.
Support-Vector Networks, in: Machine Learning, 1995, vol. 20, p. 273–297.
V. Gupta, R. Jagadeesan, V. Saraswat.
Computing with Continuous Change, in: Science of computer programming, 1998, vol. 30, no 1-2, p. 3-49.
V. A. Saraswat.
Concurrent constraint programming, ACM Doctoral Dissertation Awards, MIT Press, 1993.
P. van Hentenryck, V. Saraswat.
Strategic directions in constraint programming, in: ACM Computing Surveys, 1996, vol. 28, no 4, p. 701–726.
V. Vapnik.
Estimation of Dependences Based on Empirical Data., Springer-Verlag, N.Y., 1982.
V. Vapnik.
Statistical learning theory, John Wiley & Sons, Inc., N.Y., 1998.