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Multi-task learning (MTL) has achieved success over a wide range of problems, where the goal is to improve the performance of a primary task using a set of relevant auxiliary tasks.
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An empirical evaluation of thompson sampling
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Portfolio allocation for bayesian optimization
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Jasper Snoek, Hugo Larochelle, and Ryan P Adams. 2012 · 2012
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Kevin Swersky, Jasper Snoek, and Ryan P Adams. 2013 · 2012
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Adaptation data selection using neural language models: Experiments in machine translation
Kevin Duh, Graham Neubig, Katsuhito Sudoh, and Hajime Tsukada. 2013 · 2013
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Adam: A method for stochastic optimization
Diederik P. Kingma and Jimmy Ba. 2014 · 2014
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Fast r-cnn
Ross Girshick. 2015 · 2015
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Multi-task sequence to sequence learning
Minh-Thang Luong, Quoc V Le, Ilya Sutskever, Oriol Vinyals, and Lukasz Kaiser. 2015 · 2015
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Actor-mimic: Deep multitask and transfer reinforcement learning
Emilio Parisotto, Jimmy Lei Ba, and Ruslan Salakhutdinov. 2015 · 2015
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Instance-aware semantic segmentation via multi-task network cascades
Jifeng Dai, Kaiming He, and Jian Sun. 2016 · 2016
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GPflowOpt: A Bayesian Optimization Library using TensorFlow
Nicolas Knudde, Joachim van der Herten, Tom Dhaene, and Ivo Couckuyt. 2017 · 2017
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Multi-task video captioning with video and entailment generation
Ramakanth Pasunuru and Mohit Bansal. 2017 · 2017
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Towards improving abstractive summarization via entailment generation
Ramakanth Pasunuru, Han Guo, and Mohit Bansal. 2017 · 2017
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Taming non-stationary bandits: A bayesian approach
Vishnu Raj and Sheetal Kalyani. 2017 · 2017
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Learning to select data for transfer learning with bayesian optimization
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Vime: Variational information maximizing exploration
Rein Houthooft, Xi Chen, Yan Duan, John Schulman, Filip De Turck, and Pieter Abbeel. 2016 · 2016
Cited alongside, same era.
Reinforcement learning with unsupervised auxiliary tasks
Max Jaderberg, Volodymyr Mnih, Wojciech Marian Czarnecki, Tom Schaul, Joel Z Leibo, David Silver, and Koray Kavukcuoglu. 2016 · 2016
Cited alongside, same era.
Cross-stitch networks for multi-task learning
Ishan Misra, Abhinav Shrivastava, Abhinav Gupta, and Martial Hebert. 2016 · 2016
Cited alongside, same era.
Taking the human out of the loop: A review of bayesian optimization
Bobak Shahriari, Kevin Swersky, Ziyu Wang, Ryan P Adams, and Nando De Freitas. 2016 · 2016
Cited alongside, same era.
Learning the curriculum with bayesian optimization for task-specific word representation learning
Yulia Tsvetkov, Manaal Faruqui, Wang Ling, Brian MacWhinney, and Chris Dyer. 2016 · 2016
Cited alongside, same era.
Identifying beneficial task relations for multi-task learning in deep neural networks
Joachim Bingel and Anders Søgaard. 2017 · 2017
Cited alongside, same era.
Supervised learning of universal sentence representations from natural language inference data
Alexis Conneau, Douwe Kiela, Holger Schwenk, Loic Barrault, and Antoine Bordes. 2017 · 2017
Cited alongside, same era.
Sebastian Ruder and Barbara Plank. 2017 · 2017
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Online multi-task learning using active sampling
Sahil Sharma and Balaraman Ravindran. 2017 · 2017
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Distral: Robust multitask reinforcement learning
Yee Teh, Victor Bapst, Wojciech M Czarnecki, John Quan, James Kirkpatrick, Raia Hadsell, Nicolas Heess, and Razvan Pascanu. 2017 · 2017
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Dynamic data selection for neural machine translation
Marlies van der Wees, Arianna Bisazza, and Christof Monz. 2017 · 2017
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Limbo: A Flexible High-performance Library for Gaussian Processes modeling and Data-Efficient Optimization
A. Cully, K. Chatzilygeroudis, F. Allocati, and J.-B. Mouret. 2018 · 2018
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Dynamic multi-level multi-task learning for sentence simplification
Han Guo, Ramakanth Pasunuru, and Mohit Bansal. 2018 · 2018
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The natural language decathlon: Multitask learning as question answering
Bryan McCann, Nitish Shirish Keskar, Caiming Xiong, and Richard Socher. 2018 · 2018
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Deep contextualized word representations
Matthew E. Peters, Mark Neumann, Mohit Iyyer, Matt Gardner, Christopher Clark, Kenton Lee, and Luke Zettlemoyer. 2018 · 2018
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A tutorial on thompson sampling
Daniel J Russo, Benjamin Van Roy, Abbas Kazerouni, Ian Osband, Zheng Wen, et al. 2018 · 2018
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A tutorial on gaussian process regression: Modelling, exploring, and exploiting functions
Eric Schulz, Maarten Speekenbrink, and Andreas Krause. 2018 · 2018
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Glue: A multi-task benchmark and analysis platform for natural language understanding
Alex Wang, Amapreet Singh, Julian Michael, Felix Hill, Omer Levy, and Samuel R Bowman. 2018 · 2018
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Gated multi-task network for text classification
Liqiang Xiao, Honglun Zhang, and Wenqing Chen. 2018 · 2018
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