Nonlinear functional regression: a functional RKHS approach

By Hachem Kadri, Emmanuel Duflos, Philippe Preux, Stéphane Canu, Manuel Davy. 2010

62 citations recorded by the source corpus.

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Citations in the corpus

Learning Theory for Distribution Regression (2014, background): “, 2005), prediction of the daily precipitation profiles of weather stations (Kadri et al., 2010), acoustic-to-articulatory speech inversion (Kadri et al.”
Operator-valued Kernels for Learning from Functional Response Data (2015, methodology): “Multiplication operator: In Kadri et al. (2010), the authors attempted to extend the widely used Gaussian kernel to functional data domain using a multiplication operator and assuming that input and output data belong to the same space of functions.”
Multiple Operator-valued Kernel Learning (2012, methodology): “Before describing the multiple operator-valued kernel learning algorithm that we will study and experiment with in this paper, we first review notions and properties of reproducing kernel Hilbert spaces with operator-valued kernels, show their connection to learning from multiple response data (mult”
A Generalized Kernel Approach to Structured Output Learning (2012, background): “These kernel spaces have recently received more attention, since they are suitable for leaning in problems where the outputs are vectors (as in multitask learning (Evgeniou et al., 2005)) or functions (as in functional regression (Kadri et al., 2010)) instead of scalars.”
Input Output Kernel Regression (2016, background): “…et al. (2008); Carmeli et al. (2010)) and developed in di ↵ erent contexts such as structured classiﬁcation (Dinuzzo et al., 2011), functional regression (Kadri et al., 2010), link prediction (Brouard et al., 2011) or semi-supervised learning (Minh and Sindhwani, 2011; Brouard et al., 2011).”
Functional-bandwidth kernel for Support Vector Machine with Functional Data: An alternating optimization algorithm (2019, unknown): “The expression (3) of the Gaussian kernel for data in R d has been generalised to a Gaussian kernel for functional data, e.g. [ 35, 60].”
Fast Function to Function Regression (2014, background): “Moreover, assume that (4) holds and ni,mi n.”
Support Distribution Machines (2012, methodology): “Inspired by this, Lian (2007) and Kadri et al. (2010) generalized the functional regression problem to functional responses as well.”
Semi-supervised Penalized Output Kernel Regression for Link Prediction (2011, unknown): “In this work, the RKHS theory with vector-valued functions provides us with a general framework for OKR.”