Publications related to Total variation

Penalising the biases in norm regularisation enforces sparsity

Nicolas Henri Bernard Flammarion, Etienne Patrice Boursier

Controlling the parameters' norm often yields good generalisation when training neural networks. Beyond simple intuitions, the relation between parameters' norm and obtained estimators theoretically remains misunderstood. For one hidden ReLU layer networks ...

2023

On the Maximum Power Density of Implanted Antennas within Simplified Body Phantoms

Anja Skrivervik, Zvonimir Sipus, Mingxiang Gao

With the application requirements of wireless technology in implantable bioelectronics, knowledge of the fundamental limits for implanted antennas becomes critical. In this work, we investigated the variation of maximum power density within simplified body ...

IEEE2022

An Efficient Sampling Algorithm for Non-smooth Composite Potentials

Nicolas Henri Bernard Flammarion

We consider the problem of sampling from a density of the form p(x) ? exp(-f (x) - g(x)), where f : Rd-+ R is a smooth function and g : R-d-+ R is a convex and Lipschitz function. We propose a new algorithm based on the Metropolis-Hastings framework. Under ...

MICROTOME PUBL2022

Random Surface Covariance Estimation by Shifted Partial Tracing

Victor Panaretos, Tomas Masák

The problem of covariance estimation for replicated surface-valued processes is examined from the functional data analysis perspective. Considerations of statistical and computational efficiency often compel the use of separability of the covariance, even ...

TAYLOR & FRANCIS INC2022

Equivalence Checking for Orthocomplemented Bisemilattices in Log-Linear Time

Viktor Kuncak, Simon Guilloud

We present a quasilinear time algorithm to decide the word problem on a natural algebraic structures we call orthocomplemented bisemilattices, a subtheory of boolean algebra. We use as a base a variation of Hopcroft, Ullman and Aho algorithm for tree isomo ...

Springer2022

Sparse non-negative super-resolution - simplified and stabilised

Armin Eftekhari, Hemant Tyagi

We consider the problem of non-negative super-resolution, which concerns reconstructing a non-negative signal x = Sigma(k )(i=1)a(i)delta(ti) from m samples of its convolution with a window function phi(s - t), of the form y(s(j)) = Sigma(k)(i=1) a(i) phi( ...

ACADEMIC PRESS INC ELSEVIER SCIENCE2021

Functional registration and local variations: Identifiability, rank, and tuning

Victor Panaretos, Anirvan Chakraborty

We develop theory and methodology for the problem of nonparametric registration of functional data that have been subjected to random deformation (warping) of their time scale. The separation of this phase variation ("horizontal" variation) from the amplit ...

2021

Locally Differentially-Private Randomized Response for Discrete Distribution Learning

Michael Christoph Gastpar, Adriano Pastore

We consider a setup in which confidential i.i.d. samples X1, . . . , Xn from an unknown finite-support distribution p are passed through n copies of a discrete privatization chan- nel (a.k.a. mechanism) producing outputs Y1, . . . , Yn. The channel law gua ...

2021

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Total variation

Penalising the biases in norm regularisation enforces sparsity

On the Maximum Power Density of Implanted Antennas within Simplified Body Phantoms

An Efficient Sampling Algorithm for Non-smooth Composite Potentials

Variational Methods For Continuous-Domain Inverse Problems: the Quest for the Sparsest Solution

Random Surface Covariance Estimation by Shifted Partial Tracing

Equivalence Checking for Orthocomplemented Bisemilattices in Log-Linear Time

Coarse graining and large-N behavior of the d-dimensional N-clock model

Sparse non-negative super-resolution - simplified and stabilised

Functional registration and local variations: Identifiability, rank, and tuning

Locally Differentially-Private Randomized Response for Discrete Distribution Learning

Graph Chatbot

Chat with Graph Search

Variational Methods For Continuous-Domain Inverse Problems: the Quest for the Sparsest Solution

Sparse non-negative super-resolution - simplified and stabilised

On the Maximum Power Density of Implanted Antennas within Simplified Body Phantoms

An Efficient Sampling Algorithm for Non-smooth Composite Potentials

Equivalence Checking for Orthocomplemented Bisemilattices in Log-Linear Time

Coarse graining and large-N behavior of the d-dimensional N-clock model

Penalising the biases in norm regularisation enforces sparsity

Functional registration and local variations: Identifiability, rank, and tuning

Random Surface Covariance Estimation by Shifted Partial Tracing

Locally Differentially-Private Randomized Response for Discrete Distribution Learning