Incremental learning of evolving fuzzy inference systems : application to handwritten gesture recognition, Institut National des Sciences Appliquées (INSA) de Rennes, 2011. ,
Fast Incremental Learning Strategy Driven by Confusion Reject for Online Handwriting Recognition, 2009 10th International Conference on Document Analysis and Recognition, pp.81-85, 2009. ,
DOI : 10.1109/ICDAR.2009.23
URL : https://hal.archives-ouvertes.fr/hal-00491335
Improving premise structure in evolving takagi-sugeno neuro-fuzzy classifiers, Proceedings of the Ninth International Conference on Machine Learning and Applications, 2010. ,
URL : https://hal.archives-ouvertes.fr/hal-00741483
An Approach to Online Identification of Takagi-Sugeno Fuzzy Models, IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics), vol.34, issue.1, pp.484-498, 2004. ,
DOI : 10.1109/TSMCB.2003.817053
Evolving fuzzy-rule-based classifiers from data streams. Fuzzy Systems, IEEE Transactions on, vol.16, issue.6, pp.1462-1475, 2008. ,
Incremental and Decremental Multi-category Classification by Support Vector Machines, 2009 International Conference on Machine Learning and Applications, pp.294-300, 2009. ,
DOI : 10.1109/ICMLA.2009.114
Apprentissage artificiel : concepts et algorithmes Eyrolles, Algorithmes, 2002. ,
Implementation of self-tuning regulators with variable forgetting factors, Automatica, vol.17, issue.6, pp.17831-835, 1981. ,
DOI : 10.1016/0005-1098(81)90070-4
Extending the functional equivalence of radial basis function networks and fuzzy inference systems, IEEE Transactions on Neural Networks, vol.7, issue.3, pp.776-781, 1996. ,
DOI : 10.1109/72.501735
Evolving fuzzy neural networks for supervised/unsupervised on-line knowledge-based learning, 2001. ,
DENFIS: dynamic evolving neural-fuzzy inference system and its application for time-series prediction, IEEE Transactions on Fuzzy Systems, vol.10, issue.2, 2002. ,
DOI : 10.1109/91.995117
Detecting concept drift with support vector machines, Proceedings of the Seventeenth International Conference on Machine Learning (ICML), pp.487-494, 2000. ,
A practical approach for writer-dependent symbol recognition using a writer-independent symbol recognizer, IEEE Trans. Pattern Anal. Mach. Intell, issue.11, pp.291917-1926, 2007. ,
Incremental clustering of dynamic data streams using connectivity based representative points, Data & Knowledge Engineering, vol.68, issue.1, pp.1-27, 2009. ,
DOI : 10.1016/j.datak.2008.08.006
On the numerical stability and accuracy of the conventional recursive least squares algorithm, Liavas and Regalia, pp.88-96, 1999. ,
DOI : 10.1109/78.738242
Evolving fuzzy models : incremental learning, interpretability , and stability issues, applications, 2008. ,
DOI : 10.1142/9789814675017_0003
Flexfis : A robust incremental learning approach for evolving takagi-sugeno fuzzy models. Fuzzy Systems, IEEE Transactions on, vol.16, issue.6, pp.1393-1410, 2008. ,
Handling drifts and shifts in on-line data streams with evolving fuzzy systems, Applied Soft Computing, vol.11, issue.2, pp.2057-2068, 2011. ,
DOI : 10.1016/j.asoc.2010.07.003
Incremental learning with partial instance memory, Artificial Intelligence, vol.154, issue.1-2, pp.95-126, 2004. ,
DOI : 10.1016/j.artint.2003.04.001
URL : http://mars.gmu.edu/bitstream/1920/1477/2/02-01.pdf
Application of fuzzy logic to approximate reasoning using linguistic synthesis. Computers, IEEE Transactions, issue.12, pp.261182-1191, 1977. ,
Negative correlation in incremental learning, Natural Computing, vol.62, issue.1, pp.289-320, 2009. ,
DOI : 10.1007/s11047-007-9063-7
Study of the transient phase of the forgetting factor RLS, IEEE Transactions on Signal Processing, vol.45, issue.10, pp.452468-2476, 1997. ,
DOI : 10.1109/78.640712
Learn++: an incremental learning algorithm for supervised neural networks, Special Issue on Knowledge Management, pp.497-508, 2001. ,
DOI : 10.1109/5326.983933
A fast approach to novelty detection in video streams using recursive density estimation, 2008 4th International IEEE Conference Intelligent Systems, pp.14-16, 2008. ,
DOI : 10.1109/IS.2008.4670523
Improved least squares identification, International Journal of Control, vol.132, issue.6, pp.1889-1913, 1987. ,
DOI : 10.1016/0005-1098(84)90010-4
Incremental learning with support vector machines, Proceedings 2001 IEEE International Conference on Data Mining, pp.641-642, 2001. ,
DOI : 10.1109/ICDM.2001.989589
Modified least squares algorithm incorporating exponential resetting and forgetting, International Journal of Control, vol.47, issue.2, pp.47477-491, 1988. ,
DOI : 10.1080/00207178808906026
Handling concept drifts in incremental learning with support vector machines, Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining , KDD '99, pp.317-321, 1999. ,
DOI : 10.1145/312129.312267
Fuzzy identification of systems and its applications to modeling and control, IEEE Transactions on Systems, Man, and Cybernetics, vol.15, issue.1, pp.116-132, 1985. ,
DOI : 10.1109/TSMC.1985.6313399
Recursive least squares with forgetting for online estimation of vehicle mass and road grade: theory and experiments, Vehicle System Dynamics, vol.43, issue.1, pp.31-55, 2005. ,
DOI : 10.1080/00423110412331290446
Fuzzy sets, Information and Control, vol.8, issue.3, pp.338-353, 1965. ,
DOI : 10.1016/S0019-9958(65)90241-X