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Multitask learning is being increasingly adopted in applications domains like computer vision and reinforcement learning.
On the variance of the adaptive learning rate and beyond
Liyuan Liu, Haoming Jiang, Pengcheng He, Weizhu Chen, Xiaodong Liu, Jianfeng Gao, and Jiawei Han · 1908
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Multitask learning: A knowledge-based source of inductive bias
Rich Caruana · 1993
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Discovering structure in multiple learning tasks: The TC algorithm
Sebastian Thrun and Joseph O’Sullivan · 1996
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Gradient-based learning applied to document recognition
Yann LeCun, Léon Bottou, Yoshua Bengio, and Patrick Haffner · 1998
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Introductory Lectures on Convex Optimization - A Basic Course , volume 87 of Applied Optimization
Yurii E. Nesterov · 2004
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Finite-time convergent gradient flows with applications to network consensus
Jorge Cortés · 2006
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Optimization Algorithms on Matrix Manifolds
Pierre-Antoine Absil, Robert E. Mahony, and Rodolphe Sepulchre · 2008
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Learning multiple layers of features from tiny images
Alex Krizhevsky, Geoffrey Hinton, et al · 2009
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Mnist handwritten digit database
Yann LeCun, Corinna Cortes, and CJ Burges · 2010
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Reading digits in natural images with unsupervised feature learning
Yuval Netzer, Tao Wang, Adam Coates, Alessandro Bissacco, Bo Wu, and Andrew Y Ng · 2011
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Multiple-gradient descent algorithm (mgda) for multiobjective optimization
Jean-Antoine Désidéri · 2012
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Indoor semantic segmentation using depth information
Camille Couprie, Clément Farabet, Laurent Najman, and Yann LeCun · 2013
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Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2014
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Batch normalization: Accelerating deep network training by reducing internal covariate shift
Sergey Ioffe and Christian Szegedy · 2015
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Deep learning face attributes in the wild
Ziwei Liu, Ping Luo, Xiaogang Wang, and Xiaoou Tang · 2015
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Segnet: A deep convolutional encoder-decoder architecture for image segmentation
Vijay Badrinarayanan, Alex Kendall, and Roberto Cipolla · 2016
Cited alongside, same era.
Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
Cited alongside, same era.
Cross-stitch networks for multi-task learning
Ishan Misra, Abhinav Shrivastava, Abhinav Gupta, and Martial Hebert · 2016
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Gradient episodic memory for continual learning
David Lopez-Paz and Marc’Aurelio Ranzato · 2017
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An overview of multi-task learning in deep neural networks
Sebastian Ruder · 2017
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Gradnorm: Gradient normalization for adaptive loss balancing in deep multitask networks
End-to-end multi-task learning with attention
Shikun Liu, Edward Johns, and Andrew J. Davison · 2019
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Attentive single-tasking of multiple tasks
Kevis-Kokitsi Maninis, Ilija Radosavovic, and Iasonas Kokkinos · 2019
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Revisiting normalized gradient descent: Fast evasion of saddle points
Ryan W. Murray, Brian Swenson, and Soummya Kar · 2019
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Just pick a sign: Optimizing deep multitask models with gradient sign dropout
Zhao Chen, Jiquan Ngiam, Yanping Huang, Thang Luong, Henrik Kretzschmar, Yuning Chai, and Dragomir Anguelov · 2020
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Implicit learning dynamics in stackelberg games: Equilibria characterization, convergence analysis, and empirical study
Tanner Fiez, Benjamin Chasnov, and Lillian Ratliff · 2020
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Learning to branch for multi-task learning
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Zhao Chen, Vijay Badrinarayanan, Chen-Yu Lee, and Andrew Rabinovich · 2018
Cited alongside, same era.
Dynamic task prioritization for multitask learning
Michelle Guo, Albert Haque, De-An Huang, Serena Yeung, and Li Fei-Fei · 2018
Cited alongside, same era.
Multi-task learning using uncertainty to weigh losses for scene geometry and semantics
Alex Kendall, Yarin Gal, and Roberto Cipolla · 2018
Cited alongside, same era.
Multi-task learning as multi-objective optimization
Ozan Sener and Vladlen Koltun · 2018
Cited alongside, same era.
Gradient adversarial training of neural networks
Ayan Sinha, Zhao Chen, Vijay Badrinarayanan, and Andrew Rabinovich · 2018
Cited alongside, same era.
Taskonomy: Disentangling task transfer learning
Amir Roshan Zamir, Alexander Sax, William B. Shen, Leonidas J. Guibas, Jitendra Malik, and Silvio Savarese · 2018
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Trivializations for gradient-based optimization on manifolds
Mario Lezcano Casado · 2019
Cited alongside, same era.
Pengsheng Guo, Chen-Yu Lee, and Daniel Ulbricht · 2020
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What is local optimality in nonconvex-nonconcave minimax optimization?
Chi Jin, Praneeth Netrapalli, and Michael Jordan · 2020
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Which tasks should be learned together in multi-task learning?
Trevor Standley, Amir Roshan Zamir, Dawn Chen, Leonidas J. Guibas, Jitendra Malik, and Silvio Savarese · 2020
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Adashare: Learning what to share for efficient deep multi-task learning
Ximeng Sun, Rameswar Panda, Rogério Feris, and Kate Saenko · 2020
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Branched multi-task networks: Deciding what layers to share
Simon Vandenhende, Stamatios Georgoulis, Luc Van Gool, and Bert De Brabandere · 2020
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Gradient surgery for multi-task learning
Tianhe Yu, Saurabh Kumar, Abhishek Gupta, Sergey Levine, Karol Hausman, and Chelsea Finn · 2020
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Efficiently identifying task groupings for multi-task learning
Christopher Fifty, Ehsan Amid, Zhe Zhao, Tianhe Yu, Rohan Anil, and Chelsea Finn · 2021
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Variational multi-task learning with gumbel-softmax priors
Jiayi Shen, Xiantong Zhen, Marcel Worring, and Ling Shao · 2021
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Gradient vaccine: Investigating and improving multi-task optimization in massively multilingual models
Zirui Wang, Yulia Tsvetkov, Orhan Firat, and Yuan Cao · 2021
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