COBRA: A combined regression strategy
- Submitting institution
-
University College London
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 14553
- Type
- D - Journal article
- DOI
-
10.1016/j.jmva.2015.04.007
- Title of journal
- JOURNAL OF MULTIVARIATE ANALYSIS
- Article number
- -
- First page
- 18
- Volume
- 146
- Issue
- 6
- ISSN
- 0047-259X
- Open access status
- Out of scope for open access requirements
- Month of publication
- April
- Year of publication
- 2015
- URL
-
-
- Supplementary information
-
https://figshare.com/articles/Wavelet_coherence_cryptocurrency_online_indicator_data_set/5765352
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
3
- Research group(s)
-
-
- Citation count
- 11
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Introduces a radically new learning procedure to combine in a nonlinear way preliminary learners; most existing literature focuses on linear methods and this work sits at a very new corner of ensemble learning, which is an extremely popular topic in machine learning. We contribute theoretical guarantees on this new method. This work has been influential for my own research activity, having spawned three follow-up papers (including theoretical, algorithmic and applicative contributions such as image denoising), and attracted attention from the research community, leading to invited presentations in research seminars and conferences, including the annual congress of the French statistical society.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -