Selecting Useful Knowledge from Previous Tasks for Future Learning in a Single Network
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Zhongchao Shi | Peng Wang | Feifei Shi | Yong Rui | Yong Rui | Zhongchao Shi | Feifei Shi | Peng Wang
[1] Andrew Zisserman,et al. Very Deep Convolutional Networks for Large-Scale Image Recognition , 2014, ICLR.
[2] Byoung-Tak Zhang,et al. Overcoming Catastrophic Forgetting by Incremental Moment Matching , 2017, NIPS.
[3] Chrisantha Fernando,et al. PathNet: Evolution Channels Gradient Descent in Super Neural Networks , 2017, ArXiv.
[4] Marc'Aurelio Ranzato,et al. Continual Learning with Tiny Episodic Memories , 2019, ArXiv.
[5] Benjamin F. Grewe,et al. Continual learning with hypernetworks , 2019, ICLR.
[6] Svetlana Lazebnik,et al. Piggyback: Adapting a Single Network to Multiple Tasks by Learning to Mask Weights , 2018, ECCV.
[7] Yandong Guo,et al. Large Scale Incremental Learning , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[8] Razvan Pascanu,et al. Overcoming catastrophic forgetting in neural networks , 2016, Proceedings of the National Academy of Sciences.
[9] Alexandros Kalousis,et al. Continual Classification Learning Using Generative Models , 2018, NIPS 2018.
[10] Joost van de Weijer,et al. Rotate your Networks: Better Weight Consolidation and Less Catastrophic Forgetting , 2018, 2018 24th International Conference on Pattern Recognition (ICPR).
[11] Marc'Aurelio Ranzato,et al. Gradient Episodic Memory for Continual Learning , 2017, NIPS.
[12] Yi-Ming Chan,et al. Compacting, Picking and Growing for Unforgetting Continual Learning , 2019, NeurIPS.
[13] Shan Yu,et al. Continual learning of context-dependent processing in neural networks , 2018, Nature Machine Intelligence.
[14] Barbara Caputo,et al. Adding New Tasks to a Single Network with Weight Trasformations using Binary Masks , 2018, ECCV Workshops.
[15] Rama Chellappa,et al. Learning Without Memorizing , 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[16] Svetlana Lazebnik,et al. PackNet: Adding Multiple Tasks to a Single Network by Iterative Pruning , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[17] David Isele,et al. Selective Experience Replay for Lifelong Learning , 2018, AAAI.
[18] Michael S. Bernstein,et al. ImageNet Large Scale Visual Recognition Challenge , 2014, International Journal of Computer Vision.
[19] Jian Sun,et al. Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[20] Alexandros Karatzoglou,et al. Overcoming Catastrophic Forgetting with Hard Attention to the Task , 2018 .
[21] David Filliat,et al. Continual Learning for Robotics , 2019, Inf. Fusion.
[22] Pietro Perona,et al. The Caltech-UCSD Birds-200-2011 Dataset , 2011 .
[23] Tinne Tuytelaars,et al. Online Continual Learning with Maximally Interfered Retrieval , 2019, ArXiv.
[24] R. French. Catastrophic forgetting in connectionist networks , 1999, Trends in Cognitive Sciences.
[25] Derek Hoiem,et al. Learning without Forgetting , 2016, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[26] Botond Cseke,et al. Continual Learning with Bayesian Neural Networks for Non-Stationary Data , 2020, ICLR.
[27] Jiwon Kim,et al. Continual Learning with Deep Generative Replay , 2017, NIPS.
[28] Nojun Kwak,et al. StackNet: Stacking feature maps for Continual learning , 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).
[29] Surya Ganguli,et al. Continual Learning Through Synaptic Intelligence , 2017, ICML.
[30] Stefan Wermter,et al. Continual Lifelong Learning with Neural Networks: A Review , 2019, Neural Networks.
[31] Richard Socher,et al. Learn to Grow: A Continual Structure Learning Framework for Overcoming Catastrophic Forgetting , 2019, ICML.
[32] Fahad Shahbaz Khan,et al. iTAML: An Incremental Task-Agnostic Meta-learning Approach , 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[33] Lifeng Sun,et al. Adversarial Feature Alignment: Avoid Catastrophic Forgetting in Incremental Task Lifelong Learning , 2019, Neural Computation.
[34] Jonathan Krause,et al. 3D Object Representations for Fine-Grained Categorization , 2013, 2013 IEEE International Conference on Computer Vision Workshops.
[35] Yee Whye Teh,et al. Progress & Compress: A scalable framework for continual learning , 2018, ICML.
[36] Philip H. S. Torr,et al. Riemannian Walk for Incremental Learning: Understanding Forgetting and Intransigence , 2018, ECCV.
[37] Marc'Aurelio Ranzato,et al. Efficient Lifelong Learning with A-GEM , 2018, ICLR.
[38] Eric Eaton,et al. ELLA: An Efficient Lifelong Learning Algorithm , 2013, ICML.
[39] Matthew B. Blaschko,et al. Encoder Based Lifelong Learning , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).
[40] Razvan Pascanu,et al. Progressive Neural Networks , 2016, ArXiv.
[41] Andrew Zisserman,et al. Automated Flower Classification over a Large Number of Classes , 2008, 2008 Sixth Indian Conference on Computer Vision, Graphics & Image Processing.
[42] Christoph H. Lampert,et al. iCaRL: Incremental Classifier and Representation Learning , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[43] Gerald Tesauro,et al. Learning to Learn without Forgetting By Maximizing Transfer and Minimizing Interference , 2018, ICLR.
[44] Matthias De Lange,et al. Continual learning: A comparative study on how to defy forgetting in classification tasks , 2019, ArXiv.