Breaking svm complexity with crosstraining, Advances in Neural Information Processing Systems, pp.81-88, 2005. ,
Word sense disambiguation with pictures, Artificial Intelligence, vol.167, issue.1-2, pp.13-30, 2005. ,
DOI : 10.1016/j.artint.2005.04.009
Improving the convergence of backpropagation: Learning with second-order methods, Proceedings of the 1988 Connectionist Models Summer School, 1989. ,
Scaling learning algorithms towards AI, Large Scale Kernel Machines, 2007. ,
Curriculum learning, Proceedings of the 26th Annual International Conference on Machine Learning, ICML '09, p.140, 2009. ,
DOI : 10.1145/1553374.1553380
Learning Deep Architectures for AI, Machine Learning, 2009. ,
DOI : 10.1561/2200000006
Duality and geometry in SVM classifiers, Proceedings of the 17th International Conference on Machine Learning, 2000. ,
The Huller: A Simple and Efficient Online SVM, Machine Learning: ECML 2005, pp.505-512, 2005. ,
DOI : 10.1007/11564096_48
URL : https://hal.archives-ouvertes.fr/hal-00752501
Fast kernel classifiers with online and active learning, Journal of Machine Learning Research, vol.6, pp.1579-1619, 2005. ,
URL : https://hal.archives-ouvertes.fr/hal-00752361
Solving multiclass support vector machines with LaRank, Proceedings of the 24th international conference on Machine learning, ICML '07, 2007. ,
DOI : 10.1145/1273496.1273508
URL : https://hal.archives-ouvertes.fr/hal-00750277
Sequence Labelling SVMs Trained in One Pass, ECML PKDD 2008, pp.146-161, 2008. ,
DOI : 10.1007/978-3-540-87479-9_28
URL : https://hal.archives-ouvertes.fr/hal-00752369
SGD-QN: Careful quasi-Newton stochastic gradient descent, Journal of Machine Learning Research, vol.10, pp.1737-1754, 2009. ,
URL : https://hal.archives-ouvertes.fr/hal-00750911
The tradeoffs of large scale learning, Advances in Neural Information Processing Systems, 2008. ,
On-line learning for very large data sets, Applied Stochastic Models in Business and Industry, vol.14, issue.2, pp.137-151, 2005. ,
DOI : 10.1002/asmb.538
Support vector machine solvers, Large Scale Kernel Machines, pp.301-320, 2007. ,
Online algorithms and stochastic approximations, Online Learning and Neural Networks, 1998. ,
Stochastic gradient descent on toy problems, 2007. ,
Convex Optimization, 2004. ,
Query learning with large margin classifiers, Proceedings of the 17th International Conference on Machine Learning, 2000. ,
Incremental and decremental support vector machine learning, Advances in Neural Processing Systems, 2001. ,
On the algorithmic implementation of multiclass kernel-based vector machines, Journal of Machine Learning Research, vol.2, pp.265-292, 2001. ,
Ultraconservative Online Algorithms for Multiclass Problems, Journal of Machine Learning Research, vol.3, pp.951-991, 2003. ,
DOI : 10.1007/3-540-44581-1_7
Loss Bounds for Online Category Ranking, Proceedings of the 18th Annual Conference on Computational Learning Theory (COLT05), 2005. ,
DOI : 10.1007/11503415_4
Online classification on a budget, Advances in Neural Information Processing Systems, 2004. ,
Online passive-aggressive algorithms, Journal of Machine Learning Research, vol.7, pp.551-585, 2006. ,
A geometric interpretation of ?-SVM classifiers, Advances in Neural Information Processing Systems, 2000. ,
An Introduction to Support Vector Machines and other kernel-based learning methods, 2000. ,
DOI : 10.1017/CBO9780511801389
Learning as search optimization, Proceedings of the 22nd international conference on Machine learning , ICML '05, 2005. ,
DOI : 10.1145/1102351.1102373
Search-based structured prediction as classification, NIPS*Workshop on Advances in Structured Learning for Text and Speech Processing, 2005. ,
The XML document mining challenge, Advances in XML Information Retrieval and Evaluation, 5th International Workshop of the Initiative for the Evaluation of XML Retrieval (INEX06), 2006. ,
MadaBoost: a modification of AdaBoost, Proceedings of the 13th Annual Conference on Computational Learning Theory (COLT00), 2000. ,
Optimisation par descente de gradient stochastique de systèmes modulaires combinant réseaux de neurones et programmation dynamique, 1994. ,
On the sample complexity of PAC learning using random and chosen examples, Proceedings of the 3rd Annual ACM Workshop on Computational Learning Theory, 1990. ,
Learning on the border, Proceedings of the sixteenth ACM conference on Conference on information and knowledge management , CIKM '07, 2007. ,
DOI : 10.1145/1321440.1321461
Active learning for class imbalance problem, Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval, SIGIR '07, 2007. ,
DOI : 10.1145/1277741.1277927
Asymptotically Efficient Stochastic Approximation; The RM Case, The Annals of Statistics, vol.1, issue.3, pp.486-495, 1973. ,
DOI : 10.1214/aos/1176342414
Liblinear: A library for large linear classification, Journal of Machine Learning Research, vol.9, pp.1871-1874, 2008. ,
Theory of Optimal Experiments, 1972. ,
L0-The first five years of an automated language acquisition project, Artificial Intelligence Review, vol.49, issue.1-2, pp.103-129, 1996. ,
DOI : 10.1007/BF00159218
Intentional context in situated natural language learning, Proceedings of the Ninth Conference on Computational Natural Language Learning, CONLL '05, 2005. ,
DOI : 10.3115/1706543.1706562
Situated models of meaning for sports video retrieval, Human Language Technologies 2007: The Conference of the North American Chapter of the Association for Computational Linguistics; Companion Volume, Short Papers on XX, NAACL '07, 2007. ,
DOI : 10.3115/1614108.1614118
Ocas optimized cutting plane algorithm for support vector machines, Proceedings of the 25th International Machine Learning Conference (ICML08). Omnipress, 2008. ,
Large margin classification using the perceptron algorithm, Proceedings of the eleventh annual conference on Computational learning theory , COLT' 98, 1998. ,
DOI : 10.1145/279943.279985
The kernel Adatron algorithm: a fast and simple learning procedure for support vector machines, Proceedings of the 15th International Conference on Machine Learning, 1998. ,
Support vector machine classification and validation of cancer tissue samples using microarray expression data, Bioinformatics, vol.16, issue.10, pp.16906-914, 2000. ,
DOI : 10.1093/bioinformatics/16.10.906
A new approximate maximal margin classification algorithm, Journal of Machine Learning Research, vol.2, pp.213-242, 2001. ,
An Iterative Procedure for Computing the Minimum of a Quadratic Form on a Convex Set, SIAM Journal on Control, vol.4, issue.1, pp.61-79, 1966. ,
DOI : 10.1137/0304007
Parallel support vector machines: The Cascade SVM, Advances in Neural Information Processing Systems, 2005. ,
Adaptive caching by refetching, Advances in Neural Information Processing Systems, pp.1465-1472, 2003. ,
Automatic capacity tuning of very large VC-dimension classifiers, Advances in Neural Information Processing Systems, 1993. ,
Escaping the convex hull with extrapolated vector machines, Advances in Neural Information Processing Systems, pp.753-760, 2002. ,
Constraint classification for multiclass classification and ranking, Advances in Neural Information Processing Systems, pp.785-792, 2002. ,
The symbol grounding problem, Physica D: Nonlinear Phenomena, vol.42, issue.1-3, pp.335-346, 1990. ,
DOI : 10.1016/0167-2789(90)90087-6
A quadratic programming procedure, Naval Research Logistics Quarterly, vol.49, issue.1, pp.79-85, 1957. ,
DOI : 10.1002/nav.3800040113
A Fast Learning Algorithm for Deep Belief Nets, Neural Computation, vol.18, issue.7, pp.1527-1554, 2006. ,
DOI : 10.1162/jmlr.2003.4.7-8.1235
A dual coordinate descent method for large-scale linear SVM, Proceedings of the 25th international conference on Machine learning, ICML '08, 2008. ,
DOI : 10.1145/1390156.1390208
A comparison of methods for multi-class support vector machines, IEEE Transactions on Neural Networks, vol.13, pp.415-425, 2002. ,
Making large-scale SVM learning practical, Advances in Kernel Methods ? Support Vector Learning, pp.169-184, 1999. ,
The Maximum-Margin Approach to Learning Text Classifiers: Methods, Theory, and Algorithms, 2000. ,
Training linear SVMs in linear time, Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining , KDD '06, 2006. ,
DOI : 10.1145/1150402.1150429
Using string-kernels for learning semantic parsers, Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the ACL , ACL '06, 2006. ,
DOI : 10.3115/1220175.1220290
Learning language semantics from ambiguous supervision, Proceedings of the 22nd AAAI Conference on Artificial Intelligence (AAAI07), 2007. ,
Convergence of a generalized SMO algorithm for SVM classifier design, Machine Learning, vol.46, issue.1/3, pp.351-360, 2002. ,
DOI : 10.1023/A:1012431217818
A fast iterative nearest point algorithm for support vector machine classifier design, IEEE Transactions on Neural Networks, vol.11, issue.1, 1999. ,
DOI : 10.1109/72.822516
From treebank to propbank, Proceedings of the 3rd International Conference on Language Resources and Evaluation, 2002. ,
Use of support vector learning for chunk identification, Proceedings of the 2nd workshop on Learning language in logic and the 4th conference on Computational natural language learning -, 2000. ,
DOI : 10.3115/1117601.1117635
Conditional random fields: Probabilistic models for segmenting and labeling sequence data, Proceedings of the 18th International Conference on Machine Learning (ICML01), 2001. ,
Intrusion Detection in Unlabeled Data with Quarter-sphere Support Vector Machines, Proceedings of Conference on Detection of Intrusions, Malware and Vulnerability Assessment, 2004. ,
DOI : 10.1515/PIKO.2004.228
Incremental support vector learning: Analysis, implementation and applications, Journal of Machine Learning Research, vol.7, pp.1909-1936, 2006. ,
Reading checks with graph transformer networks, International Conference on Acoustics, Speech, and Signal Processing, pp.151-154, 1997. ,
Efficient backprop, Neural Networks, Tricks of the Trade, Lecture Notes in Computer Science LNCS 1524, 1998. ,
A tutorial on energy-based learning, Bak?r et al, pp.192-241, 2007. ,
RCV1: A new benchmark collection for text categorization research, Journal of Machine Learning Research, vol.5, pp.361-397, 2004. ,
The relaxed online maximum margin algorithm, Machine Learning, pp.361-387, 2002. ,
On the convergence of the decomposition method for support vector machines, IEEE Transactions on Neural Networks, vol.12, issue.6, pp.1288-1298, 2001. ,
Relating data compression and learnability, 1986. ,
Training invariant support vector machines using selective sampling, Large Scale Kernel Machines, pp.301-320, 2007. ,
Identifying suspicious URLs, Proceedings of the 26th Annual International Conference on Machine Learning, ICML '09, 2009. ,
DOI : 10.1145/1553374.1553462
Information-Based Objective Functions for Active Data Selection, Neural Computation, vol.4, issue.4, pp.589-603, 1992. ,
DOI : 10.1088/0266-5611/1/3/006
Sequence labelling with reinforcement learning and ranking algorithms, Machine Learning: ECML 2007, 2007. ,
URL : https://hal.archives-ouvertes.fr/hal-01336187
Foundations of Statistical Natural Language Processing, 1999. ,
WordNet: a lexical database for English, Communications of the ACM, vol.38, issue.11, pp.39-41, 1995. ,
DOI : 10.1145/219717.219748
Learning to connect language and perception, Proceedings of the 23rd AAAI Conference on Artificial Intelligence (AAAI08), 2008. ,
Incremental Kernel Machines for Protein Remote Homology Detection, In Hybrid Artificial Intelligence Systems, Lecture Notes in Computer Science, pp.409-416, 2009. ,
DOI : 10.1007/978-3-642-02319-4_49
Statistical analysis of learning dynamics, Signal Processing, vol.74, issue.1, pp.3-28, 1999. ,
DOI : 10.1016/S0165-1684(98)00206-0
Estimation of power consumption for household electric appliances, Proceedings of the 9th International Conference on Neural Information Processing, 2002. ICONIP '02., pp.2299-2303, 2002. ,
DOI : 10.1109/ICONIP.2002.1201903
Machine Learning, 1965. ,
DOI : 10.1017/CBO9780511819346.034
Updating quasi-Newton matrices with limited storage, Mathematics of Computation, vol.35, issue.151, pp.773-782, 1980. ,
DOI : 10.1090/S0025-5718-1980-0572855-7
On convergence proofs on perceptrons, Proceedings of the Symposium on the Mathematical Theory of Automata, 1962. ,
Fast training of support vector machines using sequential minimal optimization, Advances in Kernel Methods ? Support Vector Learning, pp.185-208, 1999. ,
Shallow semantic parsing using support vector machines, Proceedings of the North American Chapter of the Association for Computational Linguistics -Human Language Technologies (HLT-NAACL04), 2004. ,
An introduction to hidden Markov models, IEEE ASSP Magazine, vol.3, issue.1, 1986. ,
DOI : 10.1109/MASSP.1986.1165342
In defense of one-vs-all classification, Journal of Machine Learning Research, vol.5, pp.101-141, 2004. ,
The perceptron: A probabilistic model for information storage and organization in the brain., Psychological Review, vol.65, issue.6, pp.386-408, 1958. ,
DOI : 10.1037/h0042519
Connecting language to the world, Artificial Intelligence, vol.167, issue.12, pp.1-12, 2005. ,
Less is more: Active learning with support vector machines, Proceedings of the 17th International Conference on Machine Learning, 2000. ,
A stochastic quasi-Newton method for online convex optimization, Proceedings of the 11th International Conference on Artificial Intelligence and Statistics (AIstats07). Society for Artificial Intelligence and Statistics, 2007. ,
Theory of Linear and Integer Programming, 1986. ,
Shallow parsing with conditional random fields, Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology , NAACL '03, 2003. ,
DOI : 10.3115/1073445.1073473
A primal-dual perspective of online learning algorithms, Machine Learning, pp.115-142, 2007. ,
DOI : 10.1007/s10994-007-5014-x
A unified algorithmic approach for efficient online label ranking, Proceedings of the 11th International Conference on Artificial Intelligence and Statistics (AIstats07). Society for Artificial Intelligence and Statistics, 2007. ,
Pegasos, Proceedings of the 24th international conference on Machine learning, ICML '07, 2007. ,
DOI : 10.1145/1273496.1273598
Grounding language in perception, Artificial Intelligence Review, vol.12, issue.1, pp.371-391, 1994. ,
DOI : 10.1007/BF00849726
Bundle methods for machine learning, Advances in Neural Information Processing Systems, pp.1377-1384, 2008. ,
A Machine Learning Approach to Coreference Resolution of Noun Phrases, Advances in Neural Information Processing Systems, pp.521-544, 2001. ,
DOI : 10.1093/ijl/3.4.235
On termination of the SMO algorithm for support vector machines, Proceedings of International Symposium on Information Science and Electrical Engineering 2003, 2003. ,
Max-margin markov networks, Advances in Neural Information Processing Systems, 2004. ,
Learning structured prediction models, Proceedings of the 22nd international conference on Machine learning , ICML '05, 2005. ,
DOI : 10.1145/1102351.1102464
Learning structured prediction models, Proceedings of the 22nd international conference on Machine learning , ICML '05, 2004. ,
DOI : 10.1145/1102351.1102464
Artificial Perception of Actions, Cognitive Science, vol.2, issue.2, pp.117-149, 1986. ,
DOI : 10.1207/s15516709cog1002_1
Support vector machine active learning with applications to text classification, Proceedings of the 17th International Conference on Machine Learning, 2000. ,
Feature-rich part-of-speech tagging with a cyclic dependency network, Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology , NAACL '03, 2003. ,
DOI : 10.3115/1073445.1073478
Very large SVM training using core vector machines, Proceedings of the 10th International Conference on Artificial Intelligence and Statistics (AIstats05). Society for Artificial Intelligence and Statistics, 2005. ,
Large margin methods for structured and interdependent output variables, Journal of Machine Learning Research, vol.6, pp.1453-1484, 2005. ,
Ranking with ordered weighted pairwise classification, Proceedings of the 26th Annual International Conference on Machine Learning, ICML '09, 2009. ,
DOI : 10.1145/1553374.1553509
URL : https://hal.archives-ouvertes.fr/hal-01297974
Pattern recognition using generalized portrait method. Automation and Remote Control, pp.774-780, 1963. ,
Algorihms and Programs for Dependency Estimation, Nauka, 1984. ,
Estimation of Dependences Based on Empirical Data, 1982. ,
Statistical Learning Theory, 1998. ,
reCAPTCHA: Human-Based Character Recognition via Web Security Measures, Science, vol.321, issue.5895, 2008. ,
DOI : 10.1126/science.1160379
Games with a Purpose, Computer, vol.39, issue.6, pp.96-98, 2006. ,
DOI : 10.1109/MC.2006.196
Active Learning with Support Vector Machines in the Drug Discovery Process., ChemInform, vol.43, issue.22, pp.667-673, 2003. ,
DOI : 10.1002/chin.200322232
Multi-class support vector machines, 1998. ,
Online (and offline) on an even tighter budget, Proceedings of the 10th International Conference on Artificial Intelligence and Statistics (AIstats05). Society for Artificial Intelligence and Statistics, 2005. ,
URL : https://hal.archives-ouvertes.fr/hal-00752500
Understanding natural language, Cognitive Psychology, vol.3, issue.1, 1972. ,
DOI : 10.1016/0010-0285(72)90002-3
The psychology of computer vision, Pattern Recognition, vol.8, issue.3, pp.193-193, 1976. ,
DOI : 10.1016/0031-3203(76)90020-0
Learning synchronous grammars for semantic parsing with lambda calculus, Proceedings of the Annual Meeting of the Association for Computational Linguistics (ACL07), 2007. ,
On the Integration of Grounding Language and Learning Objects, Proceedings of the 19th AAAI Conference on Artificial Intelligence (AAAI04), 2004. ,
Learning to Map sentences to Logical Form: Structured Classification with Probabilistic Categorial Grammars, Proceedings of Uncertainty in Artificial Intelligence (UAI05), 2005. ,
Text chunking based on a generalization of winnow, Journal of Machine Learning Research, vol.2, pp.615-637, 2002. ,
Methods of Feasible Directions, 1960. ,
SGD-QN algorithm ranked 1 st ex-eaquo over 42 international competitors, 2007. ,
Fast Optimizers for Linear SVMs, 2008. ,