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One of the grand enduring goals of AI is to create generalist agents that can learn multiple different tasks from diverse data via multitask learning (MTL).
Discovering structure in multiple learning tasks: The tc algorithm
Sebastian Thrun and Joseph O’Sullivan · 1996
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Multitask learning
Rich Caruana · 1997
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970 million druglike small molecules for virtual screening in the chemical universe database GDB-13
L. C. Blum and J.-L. Reymond · 2009
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Multiple-gradient descent algorithm (mgda) for multiobjective optimization
Jean-Antoine Désidéri · 2012
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Indoor segmentation and support inference from rgbd images
Pushmeet Kohli Nathan Silberman, Derek Hoiem and Rob Fergus · 2012
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Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2014
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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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The cityscapes dataset for semantic urban scene understanding
Marius Cordts, Mohamed Omran, Sebastian Ramos, Timo Rehfeld, Markus Enzweiler, Rodrigo Benenson, Uwe Franke, Stefan Roth, and Bernt Schiele · 2016
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Cross-stitch networks for multi-task learning
Ishan Misra, Abhinav Shrivastava, Abhinav Gupta, and Martial Hebert · 2016
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Ubernet: Training a universal convolutional neural network for low-, mid-, and high-level vision using diverse datasets and limited memory
Iasonas Kokkinos · 2017
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Learning multiple tasks with multilinear relationship networks
Mingsheng Long, Zhangjie Cao, Jianmin Wang, and Philip S Yu · 2017
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Gradnorm: Gradient normalization for adaptive loss balancing in deep multitask networks
Zhao Chen, Vijay Badrinarayanan, Chen-Yu Lee, and Andrew Rabinovich · 2018
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Dynamic task prioritization for multitask learning
Michelle Guo, Albert Haque, De-An Huang, Serena Yeung, and Li Fei-Fei · 2018
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Soft actor-critic: Off-policy maximum entropy deep reinforcement learning with a stochastic actor
Tuomas Haarnoja, Aurick Zhou, Pieter Abbeel, and Sergey Levine · 2018
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Multi-task learning using uncertainty to weigh losses for scene geometry and semantics
Alex Kendall, Yarin Gal, and Roberto Cipolla · 2018
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Multi-task learning as multi-objective optimization
Ozan Sener and Vladlen Koltun · 2018
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Taskonomy: Disentangling task transfer learning
Amir R Zamir, Alexander Sax, William Shen, Leonidas J Guibas, Jitendra Malik, and Silvio Savarese · 2018
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Stochastic filter groups for multi-task cnns: Learning specialist and generalist convolution kernels
Felix JS Bragman, Ryutaro Tanno, Sebastien Ourselin, Daniel C Alexander, and Jorge Cardoso · 2019
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Fast graph representation learning with pytorch geometric
Matthias Fey and Jan Eric Lenssen · 2019
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End-to-end multi-task learning with attention
Shikun Liu, Edward Johns, and Andrew J Davison · 2019
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Latent multi-task architecture learning
Sebastian Ruder, Joachim Bingel, Isabelle Augenstein, and Anders Søgaard · 2019
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Automated search for resource-efficient branched multi-task networks
Efficiently identifying task groupings for multi-task learning
Chris Fifty, Ehsan Amid, Zhe Zhao, Tianhe Yu, Rohan Anil, and Chelsea Finn · 2021
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Rotograd: Dynamic gradient homogenization for multi-task learning
Adrián Javaloy and Isabel Valera · 2021
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A closer look at loss weighting in multi-task learning
Baijiong Lin, Feiyang Ye, and Yu Zhang · 2021
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Conflict-averse gradient descent for multi-task learning
Bo Liu, Xingchao Liu, Xiaojie Jin, Peter Stone, and Qiang Liu · 2021
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Improved optimization strategies for deep multi-task networks
Lucas Pascal, Pietro Michiardi, Xavier Bost, Benoit Huet, and Maria A Zuluaga · 2021
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David Bruggemann, Menelaos Kanakis, Stamatios Georgoulis, and Luc Van Gool · 2020
Cited alongside, same era.
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
Cited alongside, same era.
Mtl-nas: Task-agnostic neural architecture search towards general-purpose multi-task learning
Yuan Gao, Haoping Bai, Zequn Jie, Jiayi Ma, Kui Jia, and Wei Liu · 2020
Cited alongside, same era.
Learning to branch for multi-task learning
Pengsheng Guo, Chen-Yu Lee, and Daniel Ulbricht · 2020
Cited alongside, same era.
Follow the bisector: a simple method for multi-objective optimization
Alexandr Katrutsa, Daniil Merkulov, Nurislam Tursynbek, and Ivan Oseledets · 2020
Cited alongside, same era.
Towards impartial multi-task learning
Liyang Liu, Yi Li, Zhanghui Kuang, Jing-Hao Xue, Yimin Chen, Wenming Yang, Qingmin Liao, and Wayne Zhang · 2020
Cited alongside, same era.
Which tasks should be learned together in multi-task learning?
Trevor Standley, Amir Zamir, Dawn Chen, Leonidas Guibas, Jitendra Malik, and Silvio Savarese · 2020
Cited alongside, same era.
Variational multi-task learning with gumbel-softmax priors
Jiayi Shen, Xiantong Zhen, Marcel Worring, and Ling Shao · 2021
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Multi-task reinforcement learning with context-based representations
Shagun Sodhani, Amy Zhang, and Joelle Pineau · 2021
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Multi-task learning for dense prediction tasks: A survey
Simon Vandenhende, Stamatios Georgoulis, Wouter Van Gansbeke, Marc Proesmans, Dengxin Dai, and Luc Van Gool · 2021
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In defense of the unitary scalarization for deep multi-task learning
Vitaly Kurin, Alessandro De Palma, Ilya Kostrikov, Shimon Whiteson, and Pawan K Mudigonda · 2022
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Auto-lambda: Disentangling dynamic task relationships
Shikun Liu, Stephen James, Andrew J Davison, and Edward Johns · 2022
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Multi-task learning as a bargaining game
Aviv Navon, Aviv Shamsian, Idan Achituve, Haggai Maron, Kenji Kawaguchi, Gal Chechik, and Ethan Fetaya · 2022
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Do current multi-task optimization methods in deep learning even help?
Derrick Xin, Behrooz Ghorbani, Justin Gilmer, Ankush Garg, and Orhan Firat · 2022
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On the convergence of stochastic multi-objective gradient manipulation and beyond
Shiji Zhou, Wenpeng Zhang, Jiyan Jiang, Wenliang Zhong, Jinjie Gu, and Wenwu Zhu · 2022
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Sparks of artificial general intelligence: Early experiments with gpt-4
Sébastien Bubeck, Varun Chandrasekaran, Ronen Eldan, Johannes Gehrke, Eric Horvitz, Ece Kamar, Peter Lee, Yin Tat Lee, Yuanzhi Li, Scott Lundberg, et al · 2023
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Alexander Kirillov, Eric Mintun, Nikhila Ravi, Hanzi Mao, Chloe Rolland, Laura Gustafson, Tete Xiao, Spencer Whitehead, Alexander C Berg, Wan-Yen Lo, et al · 2023
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