Bayesian Online Multitask Learning of Gaussian Processes
By Gianluigi Pillonetto, Francesco Dinuzzo, Giuseppe De Nicolao. 2010
77 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Biophysics, Control and Systems Engineering, Probabilistic & Bayesian Methods
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Qiang Yang
- Yu Zhang
- Michael A. Osborne
- David A. Howey
- Qiang Zhou
- Robert R. Richardson
- Qi Zhao
- Mingsheng Long
In Biophysics
In Control and Systems Engineering
In Probabilistic & Bayesian Methods
Citations in the corpus
- An Overview of Multi-task Learning (2018, methodology): “In [78], a Bayesian online algorithm is proposed for a multi-task Gaussian process that shares kernel parameters among tasks.”
- A Survey on Multi-Task Learning (2017, methodology): “In [156], a recursive Bayesian online algorithm based on Gaussian processes is devised”
- Flexible Clustered Multi-Task Learning by Learning Representative Tasks (2016, background): “Extensive experimental results are presented in Section 4, followed by conclusions and future works in Section 5.”
- Gaussian process regression for forecasting battery state of health (2017, background): “However, we note various different efficient/approximate schemes have been proposed in the literature, based on approximating input data with pseudo points [24], exploiting grid structure [25] and exploiting the recursivity of the estimation problem in online settings [22,26,27]; and these could be ”