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The ability to incrementally learn new classes is crucial to the development of real-world artificial intelligence systems.
A ”neural-gas” network learns topologies
Martinetz Thomas and Schulten Klaus · 1991
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Competitive hebbian learning rule forms perfectly topology preserving maps
T. M. Martinetz · 1993
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A growing neural gas network learns topologies
Bernd Fritzke · 1995
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Catastrophic forgetting in connectionist networks
Robert M French · 1999
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The topological approach to perceptual organization
Chen Lin · 2005
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An incremental growing neural gas learns topologies
Y. Prudent and A. Ennaji · 2005
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Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, R. Socher, Li Jia Li, Kai Li, and Fei Fei Li · 2009
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Learning multiple layers of features from tiny images
Alex Krizhevsky and Geoffrey Hinton · 2009
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The Caltech-UCSD Birds-200-2011 Dataset
C Wah, S. Branson, P. Welinder, P. Perona, and S. Belongie · 2011
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Imagenet classification with deep convolutional neural networks
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton · 2012
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Caffe: Convolutional architecture for fast feature embedding
Yangqing Jia, Evan Shelhamer, Jeff Donahue, Sergey Karayev, Jonathan Long, Ross Girshick, Sergio Guadarrama, and Trevor Darrell · 2014
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2015
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Distilling the knowledge in a neural network
Geoffrey Hinton, Oriol Vinyals, and Jeff Dean · 2015
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Faster r-cnn: Towards real-time object detection with region proposal networks
Shaoqing Ren, Kaiming He, Ross Girshick, and Jian Sun · 2015
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Matching networks for one shot learning
Oriol Vinyals, Charles Blundell, Timothy Lillicrap, Koray Kavukcuoglu, and Daan Wierstra · 2016
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Rethinking atrous convolution for semantic image segmentation
Liang-Chieh Chen, George Papandreou, Florian Schroff, and Hartwig Adam · 2017
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Model-agnostic meta-learning for fast adaptation of deep networks
Chelsea Finn, Pieter Abbeel, and Sergey Levine · 2017
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Overcoming catastrophic forgetting in neural networks
James Kirkpatrick, Razvan Pascanu, Neil Rabinowitz, Joel Veness, Guillaume Desjardins, Andrei A Rusu, Kieran Milan, John Quan, Tiago Ramalho, Agnieszka Grabska-Barwinska, et al · 2017
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Overcoming catastrophic forgletting by incremental moment matching
Sang-Woo Lee, Jin-Hwa Kim, Jaehyun Jun, Jung-Woo Ha, and Byoung-Tak Zhang · 2017
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Sphereface: Deep hypersphere embedding for face recognition
Weiyang Liu, Yandong Wen, Zhiding Yu, Ming Li, Bhiksha Raj, and Le Song · 2017
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Gradient episodic memory for continual learning
David Lopez-Paz et al · 2017
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icarl: Incremental classifier and representation learning
Sylvestre-Alvise Rebuffi, Alexander Kolesnikov, Georg Sperl, and Christoph H Lampert · 2017
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Continual learning with deep generative replay
Hanul Shin, Jung Kwon Lee, Jaehong Kim, and Jiwon Kim · 2017
Packnet: Adding multiple tasks to a single network by iterative pruning
Arun Mallya and Svetlana Lazebnik · 2018
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Lifelong learning via progressive distillation and retrospection
Hou Saihui, Pan Xinyu, Loy Chen Change, Wang Zilei, and Lin Dahua · 2018
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Overcoming catastrophic forgetting with hard attention to the task
Joan Serrà, Didac Suris, Marius Miron, and Alexandros Karatzoglou · 2018
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Learning to compare: Relation network for few-shot learning
Flood Sung, Yongxin Yang, Li Zhang, Tao Xiang, Philip HS Torr, and Timothy M Hospedales · 2018
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Grassmann pooling as compact homogeneous bilinear pooling for fine-grained visual classification
Xing Wei, Yue Zhang, Yihong Gong, Jiawei Zhang, and Nanning Zheng · 2018
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Prototypical networks for few-shot learning
Jake Snell, Kevin Swersky, and Richard Zemel · 2017
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Lifelong learning with dynamically expandable networks
Jaehong Yoon, Eunho Yang, Jeongtae Lee, and Sung Ju Hwang · 2017
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Continual learning through synaptic intelligence
Friedemann Zenke, Ben Poole, and Surya Ganguli · 2017
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Memory aware synapses: Learning what (not) to forget
Rahaf Aljundi, Francesca Babiloni, Mohamed Elhoseiny, Marcus Rohrbach, and Tinne Tuytelaars · 2018
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End-to-end incremental learning
Francisco M Castro, Manuel J Marín-Jiménez, Nicolás Guil, Cordelia Schmid, and Karteek Alahari · 2018
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Efficient lifelong learning with a-gem
Arslan Chaudhry, Marc’Aurelio Ranzato, Marcus Rohrbach, and Mohamed Elhoseiny · 2018
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Memory replay gans: Learning to generate new categories without forgetting
Chenshen Wu, Luis Herranz, Xialei Liu, Joost van de Weijer, Bogdan Raducanu, et al · 2018
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Learning a unified classifier incrementally via rebalancing
Saihui Hou, Xinyu Pan, Chen Change Loy, Zilei Wang, and Dahua Lin · 2019
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Bayesian loss for crowd count estimation with point supervision
Zhiheng Ma, Xing Wei, Xiaopeng Hong, and Yihong Gong · 2019
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Visual working memory representation as a topological defined perceptual object
Wei Ning, Zhou Tiangang, Zhang Zihao, Zhuo Yan, and Chen Li · 2019
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Continual lifelong learning with neural networks: A review
German I Parisi, Ronald Kemker, Jose L Part, Christopher Kanan, and Stefan Wermter · 2019
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Incremental few-shot learning with attention attractor networks
Mengye Ren, Renjie Liao, Ethan Fetaya, and Richard Zemel · 2019
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Meta-transfer learning for few-shot learning
Qianru Sun, Yaoyao Liu, Tat-Seng Chua, and Bernt Schiele · 2019
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Large scale incremental learning
Wu Yue, Chen Yinpeng, Wang Lijuan, Ye Yuancheng, Liu Zicheng, Guo Yandong, and Fu Yun · 2019
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Lifelong gan: Continual learning for conditional image generation
Mengyao Zhai, Lei Chen, Frederick Tung, Jiawei He, Megha Nawhal, and Greg Mori · 2019
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Infrared-visible cross-modal person re-identification with an x modality
Diangang Li, Xing Wei, Xiaopeng Hong, and Yihong Gong · 2020
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Bi-objective continual learning: Learning ‘new’ while consolidating ‘known’
Xiaoyu Tao, Xiaopeng Hong, Xinyuan Chang, and Yihong Gong · 2020
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