A Statistical Learning Approach to Modal Regression
Yunlong Feng, Jun Fan, Johan A. K. Suykens
Abstract
sponsorship: The authors would like to thank the Action Editor and the reviewers for their constructive suggestions and comments that improved the quality of this paper. The research leading to these results has received funding from the European Research Council under the European Union's Seventh Framework Programme (FP7/2007-2013) / ERC AdG A-DATADRIVE-B (290923) and ERC AdG E-DUALITY (787960) under the European Union's Horizon 2020 research and innovation programme. This paper reflects only the authors' views, the Union is not liable for any use that may be made of the contained information. Research Council KUL: GOA/10/09 MaNet, CoE PFV/10/002 (OPTEC), BIL12/11T; PhD/Postdoc grants. Flemish Government: FWO: projects: G.0377.12 (Structured systems), G.088114N (Tensor based data similarity); PhD/Postdoc grants. IWT: projects: SBO POM (100031); PhD/Postdoc grants. iMinds Medical Information Technologies SBO 2014. Belgian Federal Science Policy Office: IUAP P7/19 (DYSCO, Dynamical systems, control and optimization, 2012-2017). Yunlong Feng also gratefully acknowledges the support of Simons Foundation Collaboration Grant #572064 and the Ralph E. Powe Junior Faculty Enhancement Award by Oak Ridge Associated Universities. The research of Jun Fan was supported in part by the Hong Kong RGC Early Career Schemes 22303518, and the NSF grant of China (No. 11801478). The corresponding author is Jun Fan. (European Research Council under the European Union's Seventh Framework Programme (FP7/2007-2013) / ERC AdG A-DATADRIVE-B|290923, ERC AdG E-DUALITY under the European Union's Horizon 2020 research and innovation programme|787960, Research Council KUL|GOA/10/09 MaNet, Research Council KUL|CoE PFV/10/002, Research Council KUL|BIL12/11T, Flemish Government: FWO|G.0377.12, Flemish Government: FWO|G.088114N, IWT: projects: SBO POM|100031, Belgian Federal Science Policy Office|IUAP P7/19, Simons Foundation|572064, Ralph E. Powe Junior Faculty Enhancement Award by Oak Ridge Associated Universities, Hong Kong RGC Early Career Schemes|22303518, NSF grant of China|11801478)