Abstract. We present a novel approach for nonparametric regression using wavelet basis functions. Our proposal, waveMesh, can be applied to non-equispaced data ...

We present a novel approach for nonparametric regression using wavelet basis functions. Our proposal, waveMesh, can be applied to non-equispaced data with.

Mar 11, 2019 · We present a novel approach for nonparametric regression using wavelet basis functions. Our proposal, \texttt{waveMesh}, can be applied to non-equispaced data.

Mar 11, 2019 · In this paper, we give a simple proposal that effectively extends wavelet-based methods to non- parametric modeling with a potentially large ...

We present a novel approach for nonparametric regression using wavelet basis functions. Our proposal, waveMesh, can be applied to non-equispaced data with.

Dec 3, 2018 · We present a novel approach for nonparametric regression using wavelet basis functions. Our proposal, waveMesh, can be applied to ...

Mar 11, 2019 · This work develops an efficient proximal gradient descent algorithm for computing the estimator and establishes adaptive minimax convergence ...

We present a novel approach for nonparametric regression using wavelet basisfunctions ... Wavelet regression and additive models for irregularly spaced data. open ...

We present a novel approach for nonparametric regression using wavelet basis functions.

Wavelet regression and additive models for irregularly spaced data. A Haris, A Shojaie, N Simon. Advances in neural information processing systems 31, 2018. 7 ...