Class-Incremental Learning of Convolutional Neural Networks Based on Double Consolidation Mechanism
暂无分享,去创建一个
[1] R. French. Catastrophic forgetting in connectionist networks , 1999, Trends in Cognitive Sciences.
[2] Nitish Srivastava,et al. Dropout: a simple way to prevent neural networks from overfitting , 2014, J. Mach. Learn. Res..
[3] Vasant Honavar,et al. Learn++: an incremental learning algorithm for supervised neural networks , 2001, IEEE Trans. Syst. Man Cybern. Part C.
[4] Robi Polikar,et al. Learn$^{++}$ .NC: Combining Ensemble of Classifiers With Dynamically Weighted Consult-and-Vote for Efficient Incremental Learning of New Classes , 2009, IEEE Transactions on Neural Networks.
[5] C. L. Philip Chen,et al. Broad Learning System: An Effective and Efficient Incremental Learning System Without the Need for Deep Architecture , 2018, IEEE Transactions on Neural Networks and Learning Systems.
[6] Robi Polikar,et al. Incremental Learning of Concept Drift in Nonstationary Environments , 2011, IEEE Transactions on Neural Networks.
[7] Demis Hassabis,et al. Mastering the game of Go without human knowledge , 2017, Nature.
[8] Heiko Wersing,et al. Incremental on-line learning: A review and comparison of state of the art algorithms , 2018, Neurocomputing.
[9] Sergey Ioffe,et al. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift , 2015, ICML.
[10] Joachim Denzler,et al. Fine-Tuning Deep Neural Networks in Continuous Learning Scenarios , 2016, ACCV Workshops.
[11] Gabriela Csurka,et al. Distance-Based Image Classification: Generalizing to New Classes at Near-Zero Cost , 2013, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[12] Geoffrey E. Hinton,et al. Distilling the Knowledge in a Neural Network , 2015, ArXiv.
[13] Jürgen Schmidhuber,et al. Compete to Compute , 2013, NIPS.
[14] Christophe G. Giraud-Carrier,et al. A Note on the Utility of Incremental Learning , 2000, AI Commun..
[15] A. Davis,et al. High speed underwater inspection for port and harbour security using Coda Echoscope 3D sonar , 2005, Proceedings of OCEANS 2005 MTS/IEEE.
[16] OctoMiao. Overcoming catastrophic forgetting in neural networks , 2016 .
[17] Changyin Sun,et al. A Broad Neural Network Structure for Class Incremental Learning , 2018, ISNN.
[18] Stefano Fusi,et al. Computational principles of synaptic memory consolidation , 2016, Nature Neuroscience.
[19] D. Cai,et al. An opportunistic theory of cellular and systems consolidation , 2011, Trends in Neurosciences.
[20] Andreas S. Tolias,et al. Three scenarios for continual learning , 2019, ArXiv.
[21] Max Welling,et al. Herding dynamical weights to learn , 2009, ICML '09.
[22] Shen Furao,et al. An incremental network for on-line unsupervised classification and topology learning , 2006, Neural Networks.
[23] Jeff Hawkins,et al. Special report : Can we copy the brain? - What intelligent machines need to learn from the Neocortex , 2017, IEEE Spectrum.
[24] Stefan Wermter,et al. Lifelong Learning of Spatiotemporal Representations With Dual-Memory Recurrent Self-Organization , 2018, Front. Neurorobot..
[25] Christoph H. Lampert,et al. iCaRL: Incremental Classifier and Representation Learning , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[26] Derek Hoiem,et al. Learning without Forgetting , 2016, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[27] Trevor Darrell,et al. Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation , 2013, 2014 IEEE Conference on Computer Vision and Pattern Recognition.