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Deep multitask learning boosts performance by sharing learned structure across related tasks.
Multitask learning
Caruana, R · 1998
Earlier work this paper cites.
Ensemble methods in machine learning
Dietterich, T. G · 2000
Earlier work this paper cites.
Regularized multi–task learning
Evgeniou, T. and Pontil, M · 2004
Earlier work this paper cites.
Convex multi-task feature learning
Argyriou, A., Evgeniou, T., and Pontil, M · 2008
Earlier work this paper cites.
A unified architecture for natural language processing: Deep neural networks with multitask learning
Collobert, R. and Weston, J · 2008
Earlier work this paper cites.
Transfer learning using Kolmogorov complexity: Basic theory and empirical evaluations
Mahmud, M. M. and Ray, S · 2008
Earlier work this paper cites.
JMLR , 9:2579–2605, Nov 2008
van der Maaten, L. and Hinton, G · 2008
Earlier work this paper cites.
On universal transfer learning
Mahmud, M. M. H · 2009
Earlier work this paper cites.
Algorithms for hyper-parameter optimization
Bergstra, J. S., Bardenet, R., Bengio, Y., and Kégl, B · 2011
Earlier work this paper cites.
Learning with whom to share in multi-task feature learning
Kang, Z., Grauman, K., and Sha, F · 2011
Earlier work this paper cites.
Learning word vectors for sentiment analysis
Maas, A. L., Daly, R. E., Pham, P. T., Huang, D., Ng, A. Y., and Potts, C · 2011
Earlier work this paper cites.
Learning task grouping and overlap in multi-task learning
Kumar, A. and Daumé, III, H · 2012
Earlier work this paper cites.
Practical bayesian optimization of machine learning algorithms
Snoek, J., Larochelle, H., and Adams, R. P · 2012
Earlier work this paper cites.
Adaptive dropout for training deep neural networks
Ba, J. and Frey, B · 2013
Earlier work this paper cites.
Cross-language knowledge transfer using multilingual deep neural network with shared hidden layers
Huang, J. T., Li, J., Yu, D., Deng, L., and Gong, Y · 2013
Earlier work this paper cites.
Multi-task learning in deep neural networks for improved phoneme recognition
Seltzer, M. L. and Droppo, J · 2013
Earlier work this paper cites.
Learning with pseudo-ensembles
Bachman, P., Alsharif, O., and Precup, D · 2014
Earlier work this paper cites.
Adam: A method for stochastic optimization
Kingma, D. P. and Ba, J · 2014
Earlier work this paper cites.
Exact solutions to the nonlinear dynamics of learning in deep linear neural networks
Saxe, A. M., McClelland, J. L., and Ganguli, S · 2014
Earlier work this paper cites.
Dropout: A Simple Way to Prevent Neural Networks from Overfitting
Srivastava, N., Hinton, G., Krizhevsky, A., Sutskever, I., and Salakhutdinov, R · 2014
Earlier work this paper cites.
Facial landmark detection by deep multi-task learning
Zhang, Z., Ping, L., Chen, L. C., and Xiaoou, T · 2014
Cited alongside, same era.
Keras, 2015
Chollet, F. et al · 2015
Cited alongside, same era.
Multi-task learning for multiple language translation
Dong, D., Wu, H., He, W., Yu, D., and Wang, H · 2015
Cited alongside, same era.
Distilling the Knowledge in a Neural Network
Hinton, G., Vinyals, O., and Dean, J · 2015
Cited alongside, same era.
Rapid adaptation for deep neural networks through multi-task learning
Huang, Z., Li, J., Siniscalchi, S. M., Chen, I.-F., Wu, J., and Lee, C.-H · 2015
Cited alongside, same era.
Human-level concept learning through probabilistic program induction
Lake, B. M., Salakhutdinov, R., and Tenenbaum, J. B · 2015
Cited alongside, same era.
Network morphism
Wei, T., Wang, C., Rui, Y., and Chen, C. W · 2016
Later among the works it cites.
Stack-propagation: Improved representation learning for syntax
Zhang, Y. and Weiss, D · 2016
Later among the works it cites.
Pathnet: Evolution channels gradient descent in super neural networks
Fernando, C., Banarse, D., Blundell, C., Zwols, Y., Ha, D., Rusu, A. A., Pritzel, A., and Wierstra, D · 2017
Later among the works it cites.
AFFACT - alignment free facial attribute classification technique
Günther, M., Rozsa, A., and Boult, T. E · 2017
Later among the works it cites.
Attributes for improved attributes: A multi-task network utilizing implicit and explicit relationships for facial attribute classification
Hand, E. M. and Chellappa, R · 2017
Later among the works it cites.
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Cited alongside, same era.
Gradient-based hyperparameter optimization through reversible learning
Maclaurin, D., Duvenaud, D., and Adams, R · 2015
Cited alongside, same era.
ImageNet Large Scale Visual Recognition Challenge
Russakovsky, O., Deng, J., Su, H., Krause, J., Satheesh, S., Ma, S., Huang, Z., Karpathy, A., Khosla, A., Bernstein, M., Berg, A. C., and Fei-Fei, L · 2015
Cited alongside, same era.
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Cited alongside, same era.
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Cited alongside, same era.
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Cited alongside, same era.
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Later among the works it cites.
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He, K., Wang, Z., Fu, Y., Feng, R., Jiang, Y.-G., and Xue, X · 2017
Later among the works it cites.
Kaiser, L., Gomez, A. N., Shazeer, N., Vaswani, A., Parmar, N., Jones, L., and Uszkoreit, J · 2017
Later among the works it cites.
Learning multiple tasks with multilinear relationship networks
Long, M., Cao, Z., Wang, J., and Yu, P. S · 2017
Later among the works it cites.
Fully-adaptive feature sharing in multi-task networks with applications in person attribute classification
Lu, Y., Kumar, A., Zhai, S., Cheng, Y., Javidi, T., and Feris, R. S · 2017
Later among the works it cites.
Learned in translation: Contextualized word vectors
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Later among the works it cites.
Miikkulainen, R., Liang, J., Meyerson, E., Rawal, A., Fink, D., Francon, O., Raju, B., Shahrzad, H., Navruzyan, A., Duffy, N., and Hodjat, B · 2017
Later among the works it cites.
Large-scale evolution of image classifiers
Real, E., Moore, S., Selle, A., Saxena, S., Suematsu, Y. L., Tan, J., Le, Q. V., and Kurakin, A · 2017
Later among the works it cites.
Learning multiple visual domains with residual adapters
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Later among the works it cites.
An overview of multi-task learning in deep neural networks
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Later among the works it cites.
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Later among the works it cites.
Multitask Learning with Low-Level Auxiliary Tasks for Encoder-Decoder Based Speech Recognition
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Later among the works it cites.
Deep multi-task representation learning: A tensor factorisation approach
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Later among the works it cites.
Neural architecture search with reinforcement learning
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Later among the works it cites.
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