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Deep neural networks (DNNs) are often trained on the premise that the complete training data set is provided ahead of time.
An approach to anytime learning
John J Grefenstette and Connie Loggia Ramsey · 1992
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Is learning the n-th thing any easier than learning the first?
Sebastian Thrun · 1995
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Learning multiple layers of features from tiny images
Alex Krizhevsky et al · 2009
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A survey on transfer learning
Sinno Jialin Pan and Qiang Yang · 2009
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Active learning literature survey
Burr Settles · 2009
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Forgetting is regulated through rac activity in drosophila
Yichun Shuai, Binyan Lu, Ying Hu, Lianzhang Wang, Kan Sun, and Yi Zhong · 2010
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Decay happens: the role of active forgetting in memory
Oliver Hardt, Karim Nader, and Lynn Nadel · 2013
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Intriguing properties of neural networks
Christian Szegedy, Wojciech Zaremba, Ilya Sutskever, Joan Bruna, Dumitru Erhan, Ian Goodfellow, and Rob Fergus · 2013
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Very deep convolutional networks for large-scale image recognition
Karen Simonyan and Andrew Zisserman · 2014
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Obtaining well calibrated probabilities using bayesian binning
Mahdi Pakdaman Naeini, Gregory Cooper, and Milos Hauskrecht · 2015
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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
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Sergey Zagoruyko and Nikos Komodakis · 2016
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A closer look at memorization in deep networks
Devansh Arpit, Stanisław Jastrzębski, Nicolas Ballas, David Krueger, Emmanuel Bengio, Maxinder S Kanwal, Tegan Maharaj, Asja Fischer, Aaron Courville, Yoshua Bengio, et al · 2017
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The biology of forgetting—a perspective
Ronald L Davis and Yi Zhong · 2017
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Towards deep learning models resistant to adversarial attacks
Aleksander Madry, Aleksandar Makelov, Ludwig Schmidt, Dimitris Tsipras, and Adrian Vladu · 2017
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Active learning for convolutional neural networks: A core-set approach
Ozan Sener and Silvio Savarese · 2017
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Critical learning periods in deep networks
Alessandro Achille, Matteo Rovere, and Stefano Soatto · 2018
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Three scenarios for continual learning
Gido M Van de Ven and Andreas S Tolias · 2019
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On warm-starting neural network training
Jordan Ash and Ryan P Adams · 2020
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Inductive biases for deep learning of higher-level cognition
Anirudh Goyal and Yoshua Bengio · 2020
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Multivariate confidence calibration for object detection
Fabian Kuppers, Jan Kronenberger, Amirhossein Shantia, and Anselm Haselhoff · 2020
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Rifle: Backpropagation in depth for deep transfer learning through re-initializing the fully-connected layer
Xingjian Li, Haoyi Xiong, Haozhe An, Cheng-Zhong Xu, and Dejing Dou · 2020
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Namhoon Lee, Thalaiyasingam Ajanthan, and Philip HS Torr · 2018
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Robustness may be at odds with accuracy
Dimitris Tsipras, Shibani Santurkar, Logan Engstrom, Alexander Turner, and Aleksander Madry · 2018
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Deep batch active learning by diverse, uncertain gradient lower bounds
Jordan T Ash, Chicheng Zhang, Akshay Krishnamurthy, John Langford, and Alekh Agarwal · 2019
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The forgotten part of memory
Lauren Gravitz · 2019
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Benchmarking neural network robustness to common corruptions and perturbations
Dan Hendrycks and Thomas Dietterich · 2019
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Adversarial examples are not bugs, they are features
Andrew Ilyas, Shibani Santurkar, Dimitris Tsipras, Logan Engstrom, Brandon Tran, and Aleksander Madry · 2019
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Rem sleep–active mch neurons are involved in forgetting hippocampus-dependent memories
Shuntaro Izawa, Srikanta Chowdhury, Toh Miyazaki, Yasutaka Mukai, Daisuke Ono, Ryo Inoue, Yu Ohmura, Hiroyuki Mizoguchi, Kazuhiro Kimura, Mitsuhiro Yoshioka, et al · 2019
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Ibrahim Alabdulmohsin, Hartmut Maennel, and Daniel Keysers · 2021
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Deepal: Deep active learning in python
Kuan-Hao Huang · 2021
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Knowledge evolution in neural networks
Ahmed Taha, Abhinav Shrivastava, and Larry S Davis · 2021
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On anytime learning at macroscale
Lucas Caccia, Jing Xu, Myle Ott, Marcaurelio Ranzato, and Ludovic Denoyer · 2022
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APP: Anytime Progressive Pruning
Diganta Misra, Bharat Runwal, Tianlong Chen, Zhangyang Wang, and Irina Rish · 2022
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When does re-initialization work?
Sheheryar Zaidi, Tudor Berariu, Hyunjik Kim, Jörg Bornschein, Claudia Clopath, Yee Whye Teh, and Razvan Pascanu · 2022
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Fortuitous forgetting in connectionist networks
Hattie Zhou, Ankit Vani, Hugo Larochelle, and Aaron Courville · 2022
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