47 citations · 114 across the 18 of their papers we have counts for
3 papers · 1 filter
Approximation of Lipschitz Functions using Deep Spline Neural Networks
Sebastian Neumayer, Alexis Goujon, Pakshal Bohra +1
Lipschitz-constrained neural networks have many applications in machine learning. Since designing and training expressive Lipschitz-constrained networks is very challenging, there…
Measuring Complexity of Learning Schemes Using Hessian-Schatten Total Variation
Shayan Aziznejad, Joaquim Campos, Michael Unser
In this paper, we introduce the Hessian-Schatten total variation (HTV) -- a novel seminorm that quantifies the total "rugosity" of multivariate functions. Our motivation for defini…
Multi-Kernel Regression with Sparsity Constraint
Shayan Aziznejad, Michael Unser
In this paper, we provide a Banach-space formulation of supervised learning with generalized total-variation (gTV) regularization. We identify the class of kernel functions that ar…