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This paper studies zero-shot domain adaptation where each domain is indexed on a multi-dimensional array, and we only have data from a small subset of domains.
Distributed optical-fibre sensors for the measurement of pressure, strain and temperature
Augustus James Rogers · 1988
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Jonathan Baxter · 2000
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A comparison of three methods for selecting values of input variables in the analysis of output from a computer code
Michael D McKay, Richard J Beckman, and William J Conover · 2000
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An application of information theory and error-correcting codes to fractional factorial experiments
Irad Ben-Gal and Lev B Levitin · 2001
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Generalization error bounds for collaborative prediction with low-rank matrices
Nathan Srebro, Noga Alon, and Tommi Jaakkola · 2004
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Rank, trace-norm and max-norm
Nathan Srebro and Adi Shraibman · 2005
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Exact matrix completion via convex optimization
Emmanuel J Candès and Benjamin Recht · 2009
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A simpler approach to matrix completion
Benjamin Recht · 2011
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Multilinear multitask learning
Bernardino Romera-Paredes, Hane Aung, Nadia Bianchi-Berthouze, and Massimiliano Pontil · 2013
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Learning tensors in reproducing kernel Hilbert spaces with multilinear spectral penalties
Marco Signoretto, Lieven De Lathauwer, and Johan AK Suykens · 2013
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Most tensor problems are np-hard
Christopher J Hillar and Lek-Heng Lim · 2013
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A unified perspective on multi-domain and multi-task learning
Yongxin Yang and Timothy M Hospedales · 2014
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Multitask learning meets tensor factorization: task imputation via convex optimization
Kishan Wimalawarne, Masashi Sugiyama, and Ryota Tomioka · 2014
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The benefit of multitask representation learning
Andreas Maurer, Massimiliano Pontil, and Bernardino Romera-Paredes · 2016
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First field trial of distributed fiber optical sensing and high-speed communication over an operational telecom network
Ming-Fang Huang, Milad Salemi, Yuheng Chen, Jingnan Zhao, Tiejun J Xia, Glenn A Wellbrock, Yue-Kai Huang, Giovanni Milione, Ezra Ip, Philip Ji, et al · 2019
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AutoAugment: Learning augmentation strategies from data
Ekin D Cubuk, Barret Zoph, Dandelion Mane, Vijay Vasudevan, and Quoc V Le · 2019
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High-Dimensional Statistics: A Non-asymptotic Viewpoint , volume 48
Martin J Wainwright · 2019
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Feature-critic networks for heterogeneous domain generalization
Yiying Li, Yongxin Yang, Wei Zhou, and Timothy Hospedales · 2019
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Few-shot learning via learning the representation, provably
Simon S Du, Wei Hu, Sham M Kakade, Jason D Lee, and Qi Lei · 2020
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Noisy tensor completion via the sum-of-squares hierarchy
Boaz Barak and Ankur Moitra · 2016
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Learning to compose domain-specific transformations for data augmentation
Alexander J Ratner, Henry R Ehrenberg, Zeshan Hussain, Jared Dunnmon, and Christopher Ré · 2017
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Deep multi-task representation learning: A tensor factorisation approach
Yongxin Yang and Timothy Hospedales · 2017
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Deeper, broader and artier domain generalization
Da Li, Yongxin Yang, Yi-Zhe Song, and Timothy M Hospedales · 2017
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Nilesh Tripuraneni, Michael I Jordan, and Chi Jin · 2020
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Tensor completion made practical
Allen Liu and Ankur Moitra · 2020
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Combatting out-of-distribution errors using model-agnostic meta-learning for digital pathology
Freja Fagerblom, Karin Stacke, and Jesper Molin · 2021
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