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The folded concave Laplacian spectral penalty learns block diagonal
  sparsity patterns with the strong oracle property

The folded concave Laplacian spectral penalty learns block diagonal sparsity patterns with the strong oracle property

7 July 2021
Iain Carmichael
ArXivPDFHTML

Papers citing "The folded concave Laplacian spectral penalty learns block diagonal sparsity patterns with the strong oracle property"

3 / 3 papers shown
Title
Spectral Gap Regularization of Neural Networks
Spectral Gap Regularization of Neural Networks
Edric Tam
David B. Dunson
FedML
17
0
0
06 Apr 2023
yaglm: a Python package for fitting and tuning generalized linear models
  that supports structured, adaptive and non-convex penalties
yaglm: a Python package for fitting and tuning generalized linear models that supports structured, adaptive and non-convex penalties
Iain Carmichael
T. Keefe
Naomi Giertych
Jonathan P. Williams
21
1
0
11 Oct 2021
Communities in Networks
Communities in Networks
M. A. Porter
J. Onnela
P. Mucha
GNN
86
1,071
0
22 Feb 2009
1