Print Email Facebook Twitter A Hybrid Recursive Implementation of Broad Learning With Incremental Features Title A Hybrid Recursive Implementation of Broad Learning With Incremental Features Author Liu, Di (Southeast University) Baldi, S. (TU Delft Team Bart De Schutter; Southeast University) Yu, Wenwu (Southeast University) Chen, C. L.P. (South China University of Technology) Date 2022 Abstract The broad learning system (BLS) paradigm has recently emerged as a computationally efficient approach to supervised learning. Its efficiency arises from a learning mechanism based on the method of least-squares. However, the need for storing and inverting large matrices can put the efficiency of such mechanism at risk in big-data scenarios. In this work, we propose a new implementation of BLS in which the need for storing and inverting large matrices is avoided. The distinguishing features of the designed learning mechanism are as follows: 1) the training process can balance between efficient usage of memory and required iterations (hybrid recursive learning) and 2) retraining is avoided when the network is expanded (incremental learning). It is shown that, while the proposed framework is equivalent to the standard BLS in terms of trained network weights,much larger networks than the standard BLS can be smoothly trained by the proposed solution, projecting BLS toward the big-data frontier. Subject Big databroad learning system (BLS)recursive learningtraining time To reference this document use: http://resolver.tudelft.nl/uuid:264690e8-48d0-42da-a02c-63c501ee67f7 DOI https://doi.org/10.1109/TNNLS.2020.3043110 Embargo date 2023-07-01 ISSN 2162-237X Source IEEE Transactions on Neural Networks and Learning Systems, 33 (4), 1650-1662 Bibliographical note Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public. Part of collection Institutional Repository Document type journal article Rights © 2022 Di Liu, S. Baldi, Wenwu Yu, C. L.P. Chen Files PDF A_Hybrid_Recursive_Implem ... atures.pdf 1.58 MB Close viewer /islandora/object/uuid:264690e8-48d0-42da-a02c-63c501ee67f7/datastream/OBJ/view