-
2
-
-
85019172761
-
Learning to learn by gradient descent by gradient descent
-
Marcin Andrychowicz, Misha Denil, Sergio Gomez, Matthew W Hoffman, David Pfau, Tom Schaul, and Nando de Freitas. Learning to learn by gradient descent by gradient descent. In Advances in Neural Information Processing Systems, 2016.
-
(2016)
Advances in Neural Information Processing Systems
-
-
Andrychowicz, M.1
Denil, M.2
Gomez, S.3
Hoffman, M.W.4
Pfau, D.5
Schaul, T.6
De Freitas, N.7
-
3
-
-
85047008902
-
On the optimization of a synaptic learning rule
-
Univ. of Texas
-
Samy Bengio, Yoshua Bengio, Jocelyn Cloutier, and Jan Gecsei. On the optimization of a synaptic learning rule. In Preprints Conf. Optimality in Artificial and Biological Neural Networks, pp. 6-8. Univ. of Texas, 1992.
-
(1992)
Preprints Conf. Optimality in Artificial and Biological Neural Networks
, pp. 6-8
-
-
Bengio, S.1
Bengio, Y.2
Cloutier, J.3
Gecsei, J.4
-
4
-
-
0034241361
-
Gradient-based optimization of hyperparameters
-
Yoshua Bengio. Gradient-based optimization of hyperparameters. Neural computation, 2000.
-
(2000)
Neural Computation
-
-
Bengio, Y.1
-
5
-
-
85018918773
-
Learning feed-forward one-shot learners
-
Luca Bertinetto, João F Henriques, Jack Valmadre, Philip Torr, and Andrea Vedaldi. Learning feed-forward one-shot learners. In Advances in Neural Information Processing Systems, 2016.
-
(2016)
Advances in Neural Information Processing Systems
-
-
Bertinetto, L.1
Henriques, J.F.2
Valmadre, J.3
Torr, P.4
Vedaldi, A.5
-
7
-
-
0005594495
-
Signature verification using a “Siamese” time delay neural network
-
Jane Bromley, James W Bentz, Léon Bottou, Isabelle Guyon, Yann LeCun, Cliff Moore, Eduard Säckinger, and Roopak Shah. Signature verification using a “Siamese” time delay neural network. International Journal of Pattern Recognition and Artificial Intelligence, 1993.
-
(1993)
International Journal of Pattern Recognition and Artificial Intelligence
-
-
Bromley, J.1
Bentz, J.W.2
Bottou, L.3
Guyon, I.4
LeCun, Y.5
Moore, C.6
Säckinger, E.7
Shah, R.8
-
10
-
-
1942470793
-
Multitask learning
-
Springer
-
Rich Caruana. Multitask learning. In Learning to learn. Springer, 1998.
-
(1998)
Learning to Learn
-
-
Caruana, R.1
-
12
-
-
85005987353
-
Best practices for fine-tuning visual classifiers to new domains
-
Springer
-
Brian Chu, Vashisht Madhavan, Oscar Beijbom, Judy Hoffman, and Trevor Darrell. Best practices for fine-tuning visual classifiers to new domains. In European Conference on Computer Vision workshops. Springer, 2016.
-
(2016)
European Conference on Computer Vision Workshops
-
-
Chu, B.1
Madhavan, V.2
Beijbom, O.3
Hoffman, J.4
Darrell, T.5
-
26
-
-
84949683101
-
Human-level concept learning through probabilistic program induction
-
Brenden M Lake, Ruslan Salakhutdinov, and Joshua B Tenenbaum. Human-level concept learning through probabilistic program induction. Science, 2015.
-
(2015)
Science
-
-
Lake, B.M.1
Salakhutdinov, R.2
Tenenbaum, J.B.3
-
28
-
-
77957064197
-
Catastrophic interference in connectionist networks: The sequential learning problem
-
Michael McCloskey and Neal J Cohen. Catastrophic interference in connectionist networks: The sequential learning problem. In Psychology of learning and motivation. 1989.
-
(1989)
Psychology of Learning and Motivation
-
-
McCloskey, M.1
Cohen, N.J.2
-
31
-
-
0003682772
-
-
Department of Computer Science, Laboratory for Computer Science Research, Rutgers Univ. New Jersey
-
Tom M Mitchell. The need for biases in learning generalizations. Department of Computer Science, Laboratory for Computer Science Research, Rutgers Univ. New Jersey, 1980.
-
(1980)
The Need for Biases in Learning Generalizations
-
-
Mitchell, T.M.1
-
32
-
-
0004255908
-
-
Burr Ridge, IL: McGraw Hill, 1997
-
Tom M Mitchell et al. Machine learning. 1997. Burr Ridge, IL: McGraw Hill, 1997.
-
(1997)
Machine Learning
-
-
Mitchell, T.M.1
-
36
-
-
85065127489
-
On first-order meta-learning algorithms
-
Alex Nichol, Joshua Achiam, and John Schulman. On first-order meta-learning algorithms. CoRR, 2018. URL http://arxiv.org/abs/1803.02999.
-
(2018)
CoRR
-
-
Nichol, A.1
Achiam, J.2
Schulman, J.3
-
37
-
-
85011070895
-
-
arXiv preprint
-
Aaron van den Oord, Sander Dieleman, Heiga Zen, Karen Simonyan, Oriol Vinyals, Alex Graves, Nal Kalchbrenner, Andrew Senior, and Koray Kavukcuoglu. Wavenet: A generative model for raw audio. arXiv preprint arXiv:1609.03499, 2016.
-
(2016)
Wavenet: A Generative Model for Raw Audio
-
-
Van Den Oord, A.1
Dieleman, S.2
Zen, H.3
Simonyan, K.4
Vinyals, O.5
Graves, A.6
Kalchbrenner, N.7
Senior, A.8
Kavukcuoglu, K.9
-
42
-
-
85083952964
-
Meta-learning for semi-supervised few-shot classification
-
Mengye Ren, Eleni Triantafillou, Sachin Ravi, Jake Snell, Kevin Swersky, Joshua B Tenenbaum, Hugo Larochelle, and Richard S Zemel. Meta-learning for semi-supervised few-shot classification. In International Conference on Learning Representations, 2018.
-
(2018)
International Conference on Learning Representations
-
-
Ren, M.1
Triantafillou, E.2
Ravi, S.3
Snell, J.4
Swersky, K.5
Tenenbaum, J.B.6
Larochelle, H.7
Zemel, R.S.8
-
44
-
-
84909978410
-
-
Olga Russakovsky, Jia Deng, Hao Su, Jonathan Krause, Sanjeev Satheesh, Sean Ma, Zhiheng Huang, Andrej Karpathy, Aditya Khosla, Michael Bernstein, et al. Imagenet large scale visual recognition challenge. 2015.
-
(2015)
Imagenet Large Scale Visual Recognition Challenge
-
-
Russakovsky, O.1
Deng, J.2
Su, H.3
Krause, J.4
Satheesh, S.5
Ma, S.6
Huang, Z.7
Karpathy, A.8
Khosla, A.9
Bernstein, M.10
-
45
-
-
84998717754
-
Meta-learning with memory-augmented neural networks
-
Adam Santoro, Sergey Bartunov, Matthew Botvinick, Daan Wierstra, and Timothy Lillicrap. Meta-learning with memory-augmented neural networks. In International Conference on Machine Learning, 2016.
-
(2016)
International Conference on Machine Learning
-
-
Santoro, A.1
Bartunov, S.2
Botvinick, M.3
Wierstra, D.4
Lillicrap, T.5
-
47
-
-
0346377064
-
Learning to control fast-weight memories: An alternative to dynamic recurrent networks
-
Jürgen Schmidhuber. Learning to control fast-weight memories: An alternative to dynamic recurrent networks. Neural Computation, 1992.
-
(1992)
Neural Computation
-
-
Schmidhuber, J.1
-
50
-
-
85071177320
-
-
Pablo Sprechmann, Siddhant M Jayakumar, Jack W Rae, Alexander Pritzel, Adrià Puigdomènech Badia, Benigno Uria, Oriol Vinyals, Demis Hassabis, Razvan Pascanu, and Charles Blundell. Memory-based parameter adaptation. 2018.
-
(2018)
Memory-Based Parameter Adaptation
-
-
Sprechmann, P.1
Jayakumar, S.M.2
Rae, J.W.3
Pritzel, A.4
Badia, A.P.5
Uria, B.6
Vinyals, O.7
Hassabis, D.8
Pascanu, R.9
Blundell, C.10
-
51
-
-
85061641334
-
Learning to compare: Relation network for few-shot learning
-
Flood Sung, Yongxin Yang, Li Zhang, Tao Xiang, Philip HS Torr, and Timothy M Hospedales. Learning to compare: Relation network for few-shot learning. In IEEE Conference on Computer Vision and Pattern Recognition, 2018.
-
(2018)
IEEE Conference on Computer Vision and Pattern Recognition
-
-
Sung, F.1
Yang, Y.2
Zhang, L.3
Xiang, T.4
Torr, P.H.S.5
Hospedales, T.M.6
-
54
-
-
0010687621
-
Lifelong learning algorithms
-
Springer
-
Sebastian Thrun. Lifelong learning algorithms. In Learning to learn. Springer, 1998.
-
(1998)
Learning to Learn
-
-
Thrun, S.1
-
55
-
-
0003901612
-
-
Springer Science & Business Media
-
Sebastian Thrun and Lorien Pratt. Learning to learn. Springer Science & Business Media, 1998.
-
(1998)
Learning to Learn
-
-
Thrun, S.1
Pratt, L.2
-
57
-
-
85044269699
-
End-to-end representation learning for correlation filter based tracking
-
Jack Valmadre, Luca Bertinetto, João Henriques, Andrea Vedaldi, and Philip HS Torr. End-to-end representation learning for correlation filter based tracking. In IEEE Conference on Computer Vision and Pattern Recognition, 2017.
-
(2017)
IEEE Conference on Computer Vision and Pattern Recognition
-
-
Valmadre, J.1
Bertinetto, L.2
Henriques, J.3
Vedaldi, A.4
Torr, P.H.S.5
-
60
-
-
85058677827
-
Group normalization
-
Yuxin Wu and Kaiming He. Group normalization. CoRR, 2018. URL http://arxiv.org/abs/1803.08494.
-
(2018)
CoRR
-
-
Wu, Y.1
He, K.2
|