Fetching the paper…
Reading the bibliography…
Modern machine learning suffers from catastrophic forgetting when learning new classes incrementally.
Catastrophic interference in connectionist networks: The sequential learning problem
Michael McCloskey and Neal J.Cohen · 1989
Earlier work this paper cites.
Incremental and decremental support vector machine learning
Gert Cauwenberghs and Tomaso Poggio · 2001
Earlier work this paper cites.
Learn++: An incremental learning algorithm for supervised neural networks
Robi Polikar, Lalita Upda, Satish S Upda, and Vasant Honavar · 2001
Earlier work this paper cites.
Learning multiple layers of features from tiny images
Alex Krizhevsky and Geoffrey Hinton · 2009
Earlier work this paper cites.
From n to n+ 1: Multiclass transfer incremental learning
Ilja Kuzborskij, Francesco Orabona, and Barbara Caputo · 2013
Earlier work this paper cites.
Distance-based image classification: Generalizing to new classes at near-zero cost
Thomas Mensink, Jakob Verbeek, Florent Perronnin, and Gabriela Csurka · 2013
Earlier work this paper cites.
Generative adversarial nets
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
Earlier work this paper cites.
Very deep convolutional networks for large-scale image recognition
Karen Simonyan and Andrew Zisserman · 2014
Earlier work this paper cites.
Tianjun Xiao, Jiaxing Zhang, Kuiyuan Yang, Yuxin Peng, and Zheng Zhang · 2014
Earlier work this paper cites.
Distilling the knowledge in a neural network
Geoffrey Hinton, Oriol Vinyals, and Jeffrey Dean · 2015
Earlier work this paper cites.
Imagenet large scale visual recognition challenge
Olga Russakovsky, Jia Deng, Hao Su, Jonathan Krause, Sanjeev Satheesh, Sean Ma, Zhiheng Huang, Andrej Karpathy, Aditya Khosla, Michael Bernstein, et al · 2015
Cited alongside, same era.
Tensorflow: Large-scale machine learning on heterogeneous distributed systems
Martín Abadi, Ashish Agarwal, Paul Barham, Eugene Brevdo, Zhifeng Chen, Craig Citro, Greg S Corrado, Andy Davis, Jeffrey Dean, Matthieu Devin, et al · 2016
Cited alongside, same era.
MS-Celeb-1M: A dataset and benchmark for large scale face recognition
Yandong Guo, Lei Zhang, Yuxiao Hu, Xiaodong He, and Jianfeng Gao · 2016
Cited alongside, same era.
Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
Cited alongside, same era.
Less-forgetting learning in deep neural networks
Heechul Jung, Jeongwoo Ju, Minju Jung, and Junmo Kim · 2016
Cited alongside, same era.
Gradient episodic memory for continual learning
David Lopez-Paz et al · 2017
Later among the works it cites.
Encoder based lifelong learning
Amal Rannen Ep Triki, Rahaf Aljundi, Matthew Blaschko, and Tinne Tuytelaars · 2017
Later among the works it cites.
icarl: Incremental classifier and representation learning
Sylvestre-Alvise Rebuffi, Alexander Kolesnikov, Georg Sperl, and Christoph H. Lampert · 2017
Later among the works it cites.
Continual learning with deep generative replay
Hanul Shin, Jung Kwon Lee, Jaehong Kim, and Jiwon Kim · 2017
Later among the works it cites.
Incremental learning of object detectors without catastrophic forgetting
Konstantin Shmelkov, Cordelia Schmid, and Karteek Alahari · 2017
Later among the works it cites.
A strategy for an uncompromising incremental learner
Ragav Venkatesan, Hemanth Venkateswara, Sethuraman Panchanathan, and Baoxin Li · 2017
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Learning without forgetting
Zhizhong Li and Derek Hoiem · 2016
Cited alongside, same era.
Andrei A Rusu, Neil C Rabinowitz, Guillaume Desjardins, Hubert Soyer, James Kirkpatrick, Koray Kavukcuoglu, Razvan Pascanu, and Raia Hadsell · 2016
Cited alongside, same era.
One-shot face recognition by promoting underrepresented classes
Yandong Guo and Lei Zhang · 2017
Cited alongside, same era.
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
Cited alongside, same era.
Later among the works it cites.
End-to-end incremental learning
Francisco M. Castro, Manuel J. Marin-Jimenez, Nicolas Guil, Cordelia Schmid, and Karteek Alahari · 2018
Later among the works it cites.
Lifelong metric learning
Gan Sun, Yang Cong, Ji Liu, Lianqing Liu, Xiaowei Xu, and Haibin Yu · 2018
Later among the works it cites.
Active lifelong learning with” watchdog”
Gan Sun, Yang Cong, and Xiaowei Xu · 2018
Later among the works it cites.