Concept

Non-uniform random variate generation

Publications associées (79)

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, Anant Raj

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

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

iSCHRUNK – In Silico Approach to Characterization and Reduction of Uncertainty in the Kinetic Models of Genome-scale Metabolic Networks

Vassily Hatzimanikatis, Ljubisa Miskovic, Stefano Andreozzi

Information about kinetics and enzyme activities while essential for quantitative understanding of metabolic dynamics remains rarely available and always involves uncertainty. In this work, we introduce the first computational methodology capable of determ ...

2016

Compressive Spectral Clustering

Pierre Vandergheynst, Rémi Gribonval, Gilles Puy, Nicolas Tremblay

Spectral clustering has become a popular technique due to its high performance in many contexts. It comprises three main steps: create a similarity graph between N objects to cluster, compute the first k eigenvectors of its Laplacian matrix to define a fea ...

2016

Structure of amorphous GeSe9 by neutron diffraction and first-principles molecular dynamics: Impact of trajectory sampling and size effects

Assil Bouzid, Carlo Massobrio

The structure of glassy GeSe9 was investigated by combining neutron diffraction with density-functional-theory-based first-principles molecular dynamics. In the simulations, three different models of N = 260 atoms were prepared by sampling three independen ...

Amer Inst Physics2016

The recursive Hessian sketch for adaptive filtering

Martin Vetterli, Robin Scheibler

We introduce in this paper the recursive Hessian sketch, a new adaptive filtering algorithm based on sketching the same exponentially weighted least squares problem solved by the recursive least squares algorithm. The algorithm maintains a number of sketch ...

Ieee2016

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