TY - CONF AU - Xialei Liu AU - Marc Masana AU - Luis Herranz AU - Joost Van de Weijer AU - Antonio Lopez AU - Andrew Bagdanov A2 - ICPR PY - 2018// TI - Rotate your Networks: Better Weight Consolidation and Less Catastrophic Forgetting BT - 24th International Conference on Pattern Recognition SP - 2262 EP - 2268 N2 - In this paper we propose an approach to avoiding catastrophic forgetting in sequential task learning scenarios. Our technique is based on a network reparameterization that approximately diagonalizes the Fisher Information Matrix of the network parameters. This reparameterization takes the form ofa factorized rotation of parameter space which, when used in conjunction with Elastic Weight Consolidation (which assumes a diagonal Fisher Information Matrix), leads to significantly better performance on lifelong learning of sequential tasks. Experimental results on the MNIST, CIFAR-100, CUB-200 andStanford-40 datasets demonstrate that we significantly improve the results of standard elastic weight consolidation, and that we obtain competitive results when compared to the state-of-the-art in lifelong learning without forgetting. L1 - http://refbase.cvc.uab.es/files/LMH2018.pdf UR - http://dx.doi.org/10.1109/ICPR.2018.8545895 N1 - LAMP; ADAS; 601.305; 601.109; 600.124; 600.106; 602.200; 600.120; 600.118 ID - Xialei Liu2018 ER -