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Abstract| A new theorem for the development and convergence analysis of supervised training algorithms with an adaptive learning rate for each weight is presented. Based on this theoretical result, a strategy is proposed to automatically adapt the search direction, as well as the stepsize length along the resultant search direction. This strategy is applied to some well known local learning algorithms to investigate its e ectiveness.doi:10.1109/ijcnn.2000.857808 dblp:conf/ijcnn/MagoulasPV00 fatcat:bifbxddifrdh3acc2d2t5h3ppu