Numerical continuation methods: An introduction ,

DOI : 10.1137/1.9780898719154

Generative-discriminative basis learning for medical imaging. Transaction on Medical Imaging, 2011. ,

Discriminative Parameter Estimation for Random Walks Segmentation ,

DOI : 10.1007/978-3-642-40760-4_28

URL : https://hal.archives-ouvertes.fr/hal-00856020

Nonlinear Programming -Theory and Algorithms, 1993. ,

Curriculum learning, Proceedings of the 26th Annual International Conference on Machine Learning, ICML '09, 2009. ,

DOI : 10.1145/1553374.1553380

Variation in Homeodomain DNA Binding Revealed by High-Resolution Analysis of Sequence Preferences, Cell, vol.133, issue.7, 2008. ,

DOI : 10.1016/j.cell.2008.05.024

Pattern recognition and machine learning, 2006. ,

Simultaneous object detection and ranking with weak supervision, NIPS, 2010. ,

Variational inference for Dirichlet process mixtures, Bayesian Analysis, vol.1, issue.1, 2006. ,

DOI : 10.1214/06-BA104

Combining labeled and unlabeled data with co-training, Proceedings of the eleventh annual conference on Computational learning theory , COLT' 98, p.98 ,

DOI : 10.1145/279943.279962

Active learning with statistical models, JAIR, vol.4, pp.129-145, 1996. ,

Histograms of Oriented Gradients for Human Detection, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05), 2005. ,

DOI : 10.1109/CVPR.2005.177

URL : https://hal.archives-ouvertes.fr/inria-00548512

Maximum likelihood from incomplete data via the EM algorithm, Journal of Royal Statistical Society, 1977. ,

ImageNet: A largescale hierarhical image database, CVPR, 2009. ,

A discriminatively trained, multiscale, deformable part model, 2008 IEEE Conference on Computer Vision and Pattern Recognition, 2008. ,

DOI : 10.1109/CVPR.2008.4587597

Supervised clustering with support vector machines, Proceedings of the 22nd international conference on Machine learning , ICML '05, 2005. ,

DOI : 10.1145/1102351.1102379

Primal-relaxed dual global optimization approach, Journal of Optimization Theory and Applications, vol.2, issue.2, pp.187-225, 1993. ,

DOI : 10.1007/BF00939667

Bayesian Data Analysis, 1995. ,

Decomposing a scene into geometric and semantically consistent regions, 2009 IEEE 12th International Conference on Computer Vision, 2009. ,

DOI : 10.1109/ICCV.2009.5459211

Lagrangean decomposition: A model yielding stronger lagrangean bounds, Mathematical Programming, 1987. ,

DOI : 10.1007/BF02612335

Quantification method in classification processes: Concept of structural ?-entropy. Kybernetika, 1967. ,

Shape-Based Object Localization for Descriptive Classification, International Journal of Computer Vision, vol.26, issue.5, 2009. ,

DOI : 10.1007/s11263-009-0228-y

A Fast Learning Algorithm for Deep Belief Nets, NIPS, 2006. ,

DOI : 10.1162/jmlr.2003.4.7-8.1235

Reducing the Dimensionality of Data with Neural Networks, Science, vol.313, issue.5786, 2006. ,

DOI : 10.1126/science.1127647

Maximum entropy discrimination, NIPS, 1999. ,

Regression Tree Fields — An efficient, non-parametric approach to image labeling problems, 2012 IEEE Conference on Computer Vision and Pattern Recognition, 2012. ,

DOI : 10.1109/CVPR.2012.6247950

Probability theory: The logic of science, 2003. ,

DOI : 10.1017/CBO9780511790423

Discriminative, generative and imitative learning, 2001. ,

Feature selection and dualities in maximum entropy discrimination, UAI, 2000. ,

Cutting-plane training of structural SVMs, Machine Learning, 2009. ,

DOI : 10.1007/s10994-009-5108-8

Probabilistic graphical models: Principles and techniques, 2009. ,

Efficient training for pairwise and higher order CRFs using dual decomposition, CVPR, 2011. ,

Beyond pairwise energies: Efficient optimization for higher-order MRFs, 2009 IEEE Conference on Computer Vision and Pattern Recognition, 2009. ,

DOI : 10.1109/CVPR.2009.5206846

MRF Optimization via Dual Decomposition: Message-Passing Revisited, 2007 IEEE 11th International Conference on Computer Vision, 2007. ,

DOI : 10.1109/ICCV.2007.4408890

Efficiently selecting regions for scene understanding, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2010. ,

DOI : 10.1109/CVPR.2010.5540072

Learning specific-class segmentation from diverse data, 2011 International Conference on Computer Vision, 2011. ,

DOI : 10.1109/ICCV.2011.6126446

Margin-based decomposed amortized inference, ACL, 2013. ,

Associative hierarchical CRFs for object class image segmentation, 2009 IEEE 12th International Conference on Computer Vision, 2009. ,

DOI : 10.1109/ICCV.2009.5459248

Gradient-based learning applied to document recognition, Proceedings of the IEEE, vol.86, issue.11, pp.2278-2324, 1998. ,

DOI : 10.1109/5.726791

Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations, Proceedings of the 26th Annual International Conference on Machine Learning, ICML '09, 2009. ,

DOI : 10.1145/1553374.1553453

Object recognition as ranking holistic figure-ground hypotheses, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2010. ,

DOI : 10.1109/CVPR.2010.5539839

Wiki-ly supervised part-of-speech tagging, EMNLP, 2012. ,

Action recognition from a distributed representation of pose and appearance, CVPR 2011, 2011. ,

DOI : 10.1109/CVPR.2011.5995631

Basic Concepts in Information Theory and Statistics, 1974. ,

Max-margin min-entropy models, AISTATS, 2012. ,

URL : https://hal.archives-ouvertes.fr/hal-00773602

Expectation propagation for infinite mixtures, NIPS Workshop on Nonparametric Bayesian Methods and Infinite Models, 2003. ,

Markov chain sampling methods for Dirichlet process mixture models, Journal of Computational and Graphical Statistics, 2000. ,

A View of the Em Algorithm that Justifies Incremental, Sparse, and other Variants, Learning in Graphical Models, 1999. ,

DOI : 10.1007/978-94-011-5014-9_12

Improving machine learning approaches to coreference resolution, Proceedings of the 40th Annual Meeting on Association for Computational Linguistics , ACL '02, 2002. ,

DOI : 10.3115/1073083.1073102

Analyzing the effectiveness and applicability of co-training, Proceedings of the ninth international conference on Information and knowledge management , CIKM '00 ,

DOI : 10.1145/354756.354805

Structured learning and prediction in computer vision. Foundations and Trends in Computer Graphics and Vision, 2010. ,

Articulated people detection and pose estimation: Reshaping the future, 2012 IEEE Conference on Computer Vision and Pattern Recognition, 2012. ,

DOI : 10.1109/CVPR.2012.6248052

Diversity and dissimilarity coefficients: A unified approach, Theoretical Population Biology, vol.21, issue.1, 1982. ,

DOI : 10.1016/0040-5809(82)90004-1

On measures of information and entropy, Berkeley Symposium on Mathematics, Statistics and Probability, 1961. ,

Expectation maximization algorithms for conditional likelihoods, Proceedings of the 22nd international conference on Machine learning , ICML '05, 2005. ,

DOI : 10.1145/1102351.1102446

Pegasos, Proceedings of the 24th international conference on Machine learning, ICML '07, 2009. ,

DOI : 10.1145/1273496.1273598

Tangent Prop -a formalism for specifying selected invariances in adaptive network, NIPS, 1991. ,

Kernel methods for missing variables, AISTATS, 2005. ,

On the convergence of concave-convex procedure, NIPS Workshop on Optimization for Machine Learning, 2009. ,

Maximum likelihood theory for incomplete data from an exponential family, Scandinavian Journal of Statistics, 1974. ,

Max-margin Markov networks, NIPS, 2003. ,

Support vector machine active learning with applications to text classification, JMLR, vol.2, pp.45-66, 2001. ,

Support vector machine learning for interdependent and structured output spaces, Twenty-first international conference on Machine learning , ICML '04, 2004. ,

DOI : 10.1145/1015330.1015341

Learning structural SVMs with latent variables, Proceedings of the 26th Annual International Conference on Machine Learning, ICML '09, 2009. ,

DOI : 10.1145/1553374.1553523

The Concave-Convex Procedure, Neural Computation, vol.39, issue.4, 2003. ,

DOI : 10.1162/08997660260028674

Learning from M/EEG Data with Variable Brain Activation Delays, IPMI, 2013. ,

DOI : 10.1007/978-3-642-38868-2_35

URL : https://hal.archives-ouvertes.fr/hal-00803981

Maximum margin clustering made practical, Proceedings of the 24th international conference on Machine learning, ICML '07, 2007. ,

DOI : 10.1145/1273496.1273637