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Lifelong learning requires models that can continuously learn from sequential streams of data without suffering catastrophic forgetting due to shifts in data distributions.
Learning and evaluating general linguistic intelligence
Dani Yogatama, Cyprien de Masson d’Autume, Jerome Connor, Tomás Kociský, Mike Chrzanowski, Lingpeng Kong, Angeliki Lazaridou, Wang Ling, Lei Yu, Chris Dyer, and Phil Blunsom. 2019 · 1901
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Learning to few-shot learn across diverse natural language classification tasks
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Evolutionary principles in self-referential learning. on learning now to learn: The meta-meta-meta…-hook
Jurgen Schmidhuber. 1987 · 1987
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Catastrophic interference in connectionist networks: The sequential learning problem
Michael McCloskey and Neal J. Cohen. 1989 · 1989
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Connectionist models of recognition memory: constraints imposed by learning and forgetting functions
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Learning a synaptic learning rule
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Self-improving reactive agents based on reinforcement learning, planning and teaching
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Multitask learning
Rich Caruana. 1997 · 1997
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Long short-term memory
Sepp Hochreiter and Jürgen Schmidhuber. 1997 · 1997
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Lifelong learning algorithms
Sebastian Thrun. 1998 · 1998
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Learning to Learn
Sebastian Thrun and Lorien Pratt. 1998 · 1998
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Catastrophic forgetting in connectionist networks
Robert M French. 1999 · 1999
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Shawn Beaulieu, Lapo Frati, Thomas Miconi, Joel Lehman, Kenneth O Stanley, Jeff Clune, and Nick Cheney. 2020 · 2002
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What happens to BERT embeddings during fine-tuning?
Amil Merchant, Elahe Rahimtoroghi, Ellie Pavlick, and Ian Tenney. 2020 · 2004
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icarl: Incremental classifier and representation learning
Sylvestre-Alvise Rebuffi, Alexander Kolesnikov, Georg Sperl, and Christoph H Lampert. 2017 · 2010
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Glove: Global vectors for word representation
Jeffrey Pennington, Richard Socher, and Christopher Manning. 2014 · 2014
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Adam: A method for stochastic optimization
Diederik P. Kingma and Jimmy Ba. 2015 · 2015
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Character-level convolutional networks for text classification
Xiang Zhang, Junbo Zhao, and Yann LeCun. 2015 · 2015
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Net2net: Accelerating learning via knowledge transfer
Tianqi Chen, Ian J. Goodfellow, and Jonathon Shlens. 2016 · 2016
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Andrei A Rusu, Neil C Rabinowitz, Guillaume Desjardins, Hubert Soyer, James Kirkpatrick, Koray Kavukcuoglu, Razvan Pascanu, and Raia Hadsell. 2016 · 2016
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Matching networks for one shot learning
Oriol Vinyals, Charles Blundell, Timothy Lillicrap, Koray Kavukcuoglu, and Daan Wierstra. 2016 · 2016
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Pathnet: Evolution channels gradient descent in super neural networks
Chrisantha Fernando, Dylan Banarse, Charles Blundell, Yori Zwols, David Ha, Andrei A. Rusu, Alexander Pritzel, and Daan Wierstra. 2017 · 2017
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Model-agnostic meta-learning for fast adaptation of deep networks
Chelsea Finn, Pieter Abbeel, and Sergey Levine. 2017 · 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 · 2017
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Gradient episodic memory for continual learning
David Lopez-Paz and Marc’Aurelio Ranzato. 2017 · 2017
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Efficient lifelong learning with A-GEM
Arslan Chaudhry, Marc’Aurelio Ranzato, Marcus Rohrbach, and Mohamed Elhoseiny. 2019 · 2019
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Episodic memory in lifelong language learning
Cyprien de Masson d’Autume, Sebastian Ruder, Lingpeng Kong, and Dani Yogatama. 2019 · 2019
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BERT: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
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Investigating meta-learning algorithms for low-resource natural language understanding tasks
Zi-Yi Dou, Keyi Yu, and Antonios Anastasopoulos. 2019 · 2019
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Meta-learning representations for continual learning
Khurram Javed and Martha White. 2019 · 2019
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Backpropamine: training self-modifying neural networks with differentiable neuromodulated plasticity
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Continual learning with deep generative replay
Hanul Shin, Jung Kwon Lee, Jaehong Kim, and Jiwon Kim. 2017 · 2017
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Continual learning through synaptic intelligence
Friedemann Zenke, Ben Poole, and Surya Ganguli. 2017 · 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 · 2018
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Riemannian walk for incremental learning: Understanding forgetting and intransigence
Arslan Chaudhry, Puneet K. Dokania, Thalaiyasingam Ajanthan, and Philip H. S. Torr. 2018 · 2018
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Lifelong machine learning
Zhiyuan Chen and Bing Liu. 2018 · 2018
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Towards Robust Evaluations of Continual Learning
Sebastian Farquhar and Yarin Gal. 2018 · 2018
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Meta-learning for low-resource neural machine translation
Jiatao Gu, Yong Wang, Yun Chen, Victor O. K. Li, and Kyunghyun Cho. 2018 · 2018
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Thomas Miconi, Aditya Rawal, Jeff Clune, and Kenneth O. Stanley. 2019 · 2019
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Meta-learning improves lifelong relation extraction
Abiola Obamuyide and Andreas Vlachos. 2019a · 2019
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Language models are unsupervised multitask learners
Alec Radford, Jeff Wu, Rewon Child, David Luan, Dario Amodei, and Ilya Sutskever. 2019 · 2019
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Adaptive posterior learning: few-shot learning with a surprise-based memory module
Tiago Ramalho and Marta Garnelo. 2019 · 2019
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Learning to learn without forgetting by maximizing transfer and minimizing interference
Matthew Riemer, Ignacio Cases, Robert Ajemian, Miao Liu, Irina Rish, Yuhai Tu, , and Gerald Tesauro. 2019 · 2019
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An empirical study of example forgetting during deep neural network learning
Mariya Toneva, Alessandro Sordoni, Remi Tachet des Combes, Adam Trischler, Yoshua Bengio, and Geoffrey J. Gordon. 2019 · 2019
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Sentence embedding alignment for lifelong relation extraction
Hong Wang, Wenhan Xiong, Mo Yu, Xiaoxiao Guo, Shiyu Chang, and William Yang Wang. 2019 · 2019
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Online continual learning from imbalanced data
Aristotelis Chrysakis and Marie-Francine Moens. 2020 · 2020
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Continual relation learning via episodic memory activation and reconsolidation
Xu Han, Yi Dai, Tianyu Gao, Yankai Lin, Zhiyuan Liu, Peng Li, Maosong Sun, and Jie Zhou. 2020 · 2020
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Learning to learn to disambiguate: Meta-learning for few-shot word sense disambiguation
Nithin Holla, Pushkar Mishra, Helen Yannakoudakis, and Ekaterina Shutova. 2020 · 2020
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Optimal continual learning has perfect memory and is np-hard
Jeremias Knoblauch, Hisham Husain, and Tom Diethe. 2020 · 2020
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Compositional language continual learning
Yuanpeng Li, Liang Zhao, Kenneth Church, and Mohamed Elhoseiny. 2020 · 2020
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Lamol: Language modeling for lifelong language learning
Fan-Keng Sun, Cheng-Hao Ho, and Hung-Yi Lee. 2020 · 2020
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Meta-dataset: A dataset of datasets for learning to learn from few examples
Eleni Triantafillou, Tyler Zhu, Vincent Dumoulin, Pascal Lamblin, Utku Evci, Kelvin Xu, Ross Goroshin, Carles Gelada, Kevin Swersky, Pierre-Antoine Manzagol, and Hugo Larochelle. 2020 · 2020
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Efficient meta lifelong-learning with limited memory
Zirui Wang, Sanket Vaibhav Mehta, Barnabas Poczos, and Jaime Carbonell. 2020 · 2020
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