Publications associées à Méthode de rejet

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

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

Handheld reflectance acquisition of paintings

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

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

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

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

Semi-Markov model for simulating MOOC students

Pierre Dillenbourg, Lukasz Kidzinski, Louis Pierre Faucon

Large-scale experiments are often expensive and time consuming. Although Massive Online Open Courses (MOOCs) provide a solid and consistent framework for learning analytics, MOOC practitioners are still reluctant to risk resources in experiments. In this s ...

2016

Sampling Sparse Signals on the Sphere: Algorithms and Applications

Yue Lu, Ivan Dokmanic

We propose a sampling scheme that can perfectly reconstruct a collection of spikes on the sphere from samples of their lowpass-filtered observations. Central to our algorithm is a generalization of the annihilating filter method, a tool widely used in arra ...

Institute of Electrical and Electronics Engineers2016

Nuclear overhauser spectroscopy of chiral CHD methylene groups

Geoffrey Bodenhausen, Fabien Ferrage

Nuclear magnetic resonance spectroscopy (NMR) can provide a great deal of information about structure and dynamics of biomolecules. The quality of an NMR structure strongly depends on the number of experimental observables and on their accurate conversion ...

Springer Verlag2016

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Méthode de rejet

Quasi-random numbers for copula models

Safe Adaptive Importance Sampling

Smooth Primal-Dual Coordinate Descent Algorithms for Nonsmooth Convex Optimization

Handheld reflectance acquisition of paintings

Extremal attractors of Liouville copulas

Riemannian Optimization For High-Dimensional Tensor Completion

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

Semi-Markov model for simulating MOOC students

Sampling Sparse Signals on the Sphere: Algorithms and Applications

Nuclear overhauser spectroscopy of chiral CHD methylene groups

Graph Chatbot

Chattez avec Graph Search

Extremal attractors of Liouville copulas

Quasi-random numbers for copula models

Handheld reflectance acquisition of paintings

Safe Adaptive Importance Sampling

Riemannian Optimization For High-Dimensional Tensor Completion

Sampling Sparse Signals on the Sphere: Algorithms and Applications

Smooth Primal-Dual Coordinate Descent Algorithms for Nonsmooth Convex Optimization

Nuclear overhauser spectroscopy of chiral CHD methylene groups

Semi-Markov model for simulating MOOC students

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