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Related publications (30)

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Random sampling of bandlimited signals on graphs

Pierre Vandergheynst, Rémi Gribonval, Gilles Puy

We study the problem of sampling k-bandlimited signals on graphs. We propose two sampling strategies that consist in selecting a small subset of nodes at random. The first strategy is non-adaptive, i.e., independent of the graph structure, and its performa ...

Elsevier2018

A Novel Method for Sampling Bandlimited Graph Signals

Pascal Frossard, Pinar Akyazi

In this paper we propose a novel vertex based sampling method for k-bandlimited signals lying on arbitrary graphs, that has a reasonable computational complexity and results in low reconstruction error. Our goal is to find the smallest set of vertices that ...

IEEE COMPUTER SOC2018

Handheld reflectance acquisition of paintings

Martin Vetterli, Sabine Süsstrunk, Loïc Arnaud Baboulaz, Niranjan Thanikachalam, Damien Firmenich

Relightable photographs are alternatives to traditional photographs as they provide a richer viewing experience. However, the complex acquisition systems of existing techniques have restricted its usage to specialized setups. We introduce an easy-to-use an ...

Ieee-Inst Electrical Electronics Engineers Inc2017

Towards Generalized FRI Sampling with an Application to Source Resolution in Radioastronomy

Martin Vetterli, Thierry Blu, Hanjie Pan

It is a classic problem to estimate continuous-time sparse signals, like point sources in a direction-of-arrival problem, or pulses in a time-of-flight measurement. The earliest occurrence is the estimation of sinusoids in time series using Prony's method. ...

Institute of Electrical and Electronics Engineers2017

Smooth Primal-Dual Coordinate Descent Algorithms for Nonsmooth Convex Optimization

Volkan Cevher, Quoc Tran Dinh, Ahmet Alacaoglu

We propose a new randomized coordinate descent method for a convex optimization template with broad applications. Our analysis relies on a novel combination of four ideas applied to the primal-dual gap function: smoothing, acceleration, homotopy, and coord ...

2017

Quasi-random numbers for copula models

Mathieu Jacques David Cambou

The present work addresses the question how sampling algorithms for commonly applied copula models can be adapted to account for quasi-random numbers. Besides sampling methods such as the conditional distribution method (based on a one-to-one transformatio ...

Springer2017

Safe Adaptive Importance Sampling

Martin Jaggi, Sebastian Urban Stich

Importance sampling has become an indispensable strategy to speed up optimization algorithms for large-scale applications. Improved adaptive variants - using importance values defined by the complete gradient information which changes during optimization - ...

2017

Nanocapillaries combined with optical tweezers as a single molecule technique for studying DNA-protein complexes

Roman Bulushev

Interactions of proteins with DNA are essential for carrying out DNA's biological functions and performing a cellular cycle. Such processes as DNA replication, expression and repair are performed by an organised action of various proteins. To better unders ...

EPFL2017

Riemannian Optimization For High-Dimensional Tensor Completion

Michael Maximilian Steinlechner

Tensor completion aims to reconstruct a high-dimensional data set where the vast majority of entries is missing. The assumption of low-rank structure in the underlying original data allows us to cast the completion problem into an optimization problem rest ...

Siam Publications2016

TRANSFORMERS: Robust Spatial Joins on Non-Uniform Data Distributions

Anastasia Ailamaki, Thomas Heinis, Farhan Tauheed, Mirjana Pavlovic

Spatial joins are becoming increasingly ubiquitous in many applications, particularly in the scientific domain. While several approaches have been proposed for joining spatial datasets, each of them has a strength for a particular type of density ratio amo ...

IEEE2016