Concept

Projecteur (mathématiques)

Publications associées (70)

Fourier dimensionality reduction for fast radio transients

Jean-Philippe Thiran, Yves Wiaux, Vijay Kartik, Ming Jiang

In the context of next-generation radio interferometers, we are facing a big challenge of how to economically process data. The classical dimensionality reduction technique, averaging visibilities on time, may dilute fast radio transients (FRT). We propose ...

2019

Almost surely constrained convex optimization

Volkan Cevher, Ahmet Alacaoglu

We propose a stochastic gradient framework for solving stochastic composite convex optimization problems with (possibly) infinite number of linear inclusion constraints that need to be satisfied almost surely. We use smoothing and homotopy techniques to ha ...

2019

Proximity Human-Robot Interaction Using Pointing Gestures and a Wrist-mounted IMU

We present a system for interaction between co-located humans and mobile robots, which uses pointing gestures sensed by a wrist-mounted IMU. The operator begins by pointing, for a short time, at a moving robot. The system thus simultaneously determines: th ...

2019

Stochastic Three-Composite Convex Minimization with a Linear Operator

Volkan Cevher

We develop a primal-dual convex minimization framework to solve a class of stochastic convex three-composite problem with a linear operator. We consider the cases where the problem is both convex and strongly convex and analyze the convergence of the propo ...

JMLR: W&CP2018

On the reverse isodiametric problem and Dvoretzky-Rogers-type volume bounds

Matthias Schymura

The isodiametric inequality states that the Euclidean ball maximizes the volume among all convex bodies of a given diameter. We are motivated by a conjecture of Makai Jr. on the reverse question: Every convex body has a linear image whose isodiametric quot ...

2018

Distributed Signal Processing via Chebyshev Polynomial Approximation

Pascal Frossard, Pierre Vandergheynst, Daniel Kressner, David Shuman

Unions of graph multiplier operators are an important class of linear operators for processing signals defined on graphs. We present a novel method to efficiently distribute the application of these operators. The proposed method features approximations of ...

2018

Landmark-Based Shape Encoding and Sparse-Dictionary Learning in the Continuous Domain

Michaël Unser, Daniel Andreas Schmitter

We provide a generic framework to learn shape dictionaries of landmark-based curves that are defined in the continuous domain. We first present an unbiased alignment method that involves the construction of a mean shape as well as training sets whose eleme ...

2018

Smoothing technique for nonsmooth composite minimization with linear operator

Volkan Cevher, Van Quang Nguyen

We introduce and analyze an algorithm for the minimization of convex functions that are the sum of differentiable terms and proximable terms composed with linear operators. The method builds upon the recently developed smoothed gap technique. In addition t ...

2017

Shape Projectors for Landmark-Based Spline Curves

Michaël Unser, Daniel Andreas Schmitter

We present a generic method to construct orthogonal projectors for two-dimensional landmark-based parametric spline curves. We construct vector spaces that define a geometric transformation (e.g., affine, similarity, and scaling) that is applied to a refer ...

2017

Towards Stationary Time-Vertex Signal Processing

Pierre Vandergheynst, Nathanaël Perraudin, Andreas Loukas, Francesco Grassi

Graph-based methods for signal processing have shown promise for the analysis of data exhibiting irregular structure, such as those found in social, transportation, and sensor networks. Yet, though these systems are often dynamic, state-of-the-art methods ...

Ieee2017

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