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Typical multi-task learning (MTL) methods rely on architectural adjustments and a large trainable parameter set to jointly optimize over several tasks.
Is learning the n-th thing any easier than learning the first?
S. Thrun · 1996
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Multitask learning
R. Caruana · 1997
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Task clustering and gating for bayesian multitask learning
B. Bakker and T. Heskes · 2003
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Multi-task learning for classification with dirichlet process priors
Y. Xue, X. Liao, L. Carin, and B. Krishnapuram · 2007
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A survey on transfer learning
S. J. Pan and Q. Yang · 2010
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The caltech-ucsd birds-200-2011 dataset
C. Wah, S. Branson, P. Welinder, P. Perona, and S. Belongie · 2011
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Random search for hyper-parameter optimization
J. Bergstra and Y. Bengio · 2012
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Regularization of neural networks using dropconnect
L. Wan, M. Zeiler, S. Zhang, Y. Le Cun, and R. Fergus · 2013
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Heterogeneous multi-task learning for human pose estimation with deep convolutional neural network
S. Li, Z.-Q. Liu, and A. B. Chan · 2014
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Very deep convolutional networks for large-scale image recognition
K. Simonyan and A. Zisserman · 2014
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Dropout: a simple way to prevent neural networks from overfitting
N. Srivastava, G. Hinton, A. Krizhevsky, I. Sutskever, and R. Salakhutdinov · 2014
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A regularization approach to learning task relationships in multitask learning
Y. Zhang and D.-Y. Yeung · 2014
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Facial landmark detection by deep multi-task learning
Z. Zhang, P. Luo, C. C. Loy, and X. Tang · 2014
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Human-level concept learning through probabilistic program induction
B. M. Lake, R. Salakhutdinov, and J. B. Tenenbaum · 2015
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Multi-task deep visual-semantic embedding for video thumbnail selection
W. Liu, T. Mei, Y. Zhang, C. Che, and J. Luo · 2015
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Xception: Deep learning with depthwise separable convolutions
F. Chollet · 2016
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Deep residual learning for image recognition
K. He, X. Zhang, S. Ren, and J. Sun · 2016
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Deep cross residual learning for multitask visual recognition
B. Jou and S.-F. Chang · 2016
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Cross-stitch networks for multi-task learning
I. Misra, A. Shrivastava, A. Gupta, and M. Hebert · 2016
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Convolutional neural fabrics
S. Saxena and J. Verbeek · 2016
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Swapout: Learning an ensemble of deep architectures
S. Singh, D. Hoiem, and D. Forsyth · 2016
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Deep multi-task representation learning: A tensor factorisation approach
Y. Yang and T. Hospedales · 2017
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Semantic jitter: Dense supervision for visual comparisons via synthetic images
A. Yu and K. Grauman · 2017
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A survey on multi-task learning
Y. Zhang and Q. Yang · 2017
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Multi-task learning by maximizing statistical dependence
Y. Alami Mejjati, D. Cosker, and K. Kim · 2018
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Dropblock: A regularization method for convolutional networks
G. Ghiasi, T.-Y. Lin, and Q. V. Le · 2018
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Learning overparameterized neural networks via stochastic gradient descent on structured data
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Deep model based transfer and multi-task learning for biological image analysis
W. Zhang, R. Li, T. Zeng, Q. Sun, S. Kumar, J. Ye, and S. Ji · 2016
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Densely connected convolutional networks
G. Huang, Z. Liu, L. Van Der Maaten, and K. Q. Weinberger · 2017
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Arbitrary style transfer in real-time with adaptive instance normalization
X. Huang and S. Belongie · 2017
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Ubernet: Training a universal convolutional neural network for low-, mid-, and high-level vision using diverse datasets and limited memory
I. Kokkinos · 2017
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Fully-adaptive feature sharing in multi-task networks with applications in person attribute classification
Y. Lu, A. Kumar, S. Zhai, Y. Cheng, T. Javidi, and R. Feris · 2017
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Latent Multi-task Architecture Learning
S. Ruder, J. Bingel, I. Augenstein, and A. Søgaard · 2017
Cited alongside, same era.
Y. Li and Y. Liang · 2018
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Evolutionary architecture search for deep multitask networks
J. Liang, E. Meyerson, and R. Miikkulainen · 2018
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Packnet: Adding multiple tasks to a single network by iterative pruning
A. Mallya and S. Lazebnik · 2018
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Regularized evolution for image classifier architecture search
E. Real, A. Aggarwal, Y. Huang, and Q. V. Le · 2018
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Motivation to comply with task rules and multitasking performance: The role of need for cognitive closure and goal importance
E. Szumowska, M. Kossowska, and A. Roets · 2018
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Multinet: Real-time joint semantic reasoning for autonomous driving
M. Teichmann, M. Weber, M. Zoellner, R. Cipolla, and R. Urtasun · 2018
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Y. Yamada, M. Iwamura, and K. Kise · 2018
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Taskonomy: Disentangling task transfer learning
A. R. Zamir, A. Sax, W. Shen, L. J. Guibas, J. Malik, and S. Savarese · 2018
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A modulation module for multi-task learning with applications in image retrieval
X. Zhao, H. Li, X. Shen, X. Liang, and Y. Wu · 2018
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Hyperface: A deep multi-task learning framework for face detection, landmark localization, pose estimation, and gender recognition
R. Ranjan, V. M. Patel, and R. Chellappa · 2019
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