Publications associées à Dynamic Partitioned Sampling For Tracking With Discriminative Features

Sampling and Exact Reconstruction of Pulses with Variable Width

Martin Vetterli, Adam James Scholefield, Loïc Arnaud Baboulaz, Gilles Baechler

Recent sampling results enable the reconstruction of signals composed of streams of fixed-shaped pulses. These results have found applications in topics as varied as channel estimation, biomedical imaging and radio astronomy. However, in many real signals, ...

Institute of Electrical and Electronics Engineers2017

On the performance of random reshuffling in stochastic learning

Ali H. Sayed, Stefan Vlaski, Bicheng Ying, Kun Yuan

In empirical risk optimization, it has been observed that gradient descent implementations that rely on random reshuffling of the data achieve better performance than implementations that rely on sampling the data randomly and independently of each other. ...

2017

Learning-based subsampling

Volkan Cevher, Jonathan Mark Scarlett, Ilija Bogunovic, Yen-Huan Li, Luca Baldassarre, Baran Gözcü

The present invention concerns a method of sampling a test signal. The method comprises: acquiring (21) training signals sampled at a plurality of sampling locations; running (23) an optimization procedure for determining an index set of n indices, represe ...

2017

Extracting the interfacial free energy and anisotropy from a smooth fluctuating dividing surface

Michele Ceriotti, Gareth Aneurin Tribello, Edoardo Baldi

Interfaces between different materials and phases play a crucial role in many physical and chemical phenomena. When performing simulations of matter at the atomic scale, however, it is often not trivial to characterize these interfaces, particularly when t ...

Iop Publishing Ltd2017

MATHICSE Technical Report : Multilevel ensemble Kalman filtering for spatio-temporal processes

Fabio Nobile, Hakon Andreas Hoel

This work concerns state-space models, in which the state-space is an infinite-dimensional spatial field, and the evolution is in continuous time, hence requiring approximation in space and time. The multilevel Monte Carlo (MLMC) sampling strategy is lever ...

MATHICSE2017

MULTILEVEL ENSEMBLE KALMAN FILTERING FOR SPATIO-TEMPORAL PROCESSES

Fabio Nobile, Hakon Andreas Hoel

This work concerns state-space models, in which the state-space is an infinite-dimensional spatial field, and the evolution is in continuous time, hence requiring approximation in space and time. The multilevel Monte Carlo (MLMC) sampling strategy is lever ...

2017

Development of the Geographical Proportional-to-size Street-Intercept Sampling (GPSIS) method for recruiting urban nightlife-goers in an entire city

Daniel Gatica-Perez, Darshan Santani

We developed the Geographical Proportional-to-size Street-Intercept Sampling (GPSIS) method in order to obtain a sample of nightlife-goers which accounted for the diversity of spaces, patrons and locations within two Swiss cities. Popular nightlife zones w ...

2017

Shapes from Pixels

Mitra Fatemi

In today's digital world, sampling is at the heart of any signal acquisition device. Imaging devices are ubiquitous examples that capture two-dimensional visual signals and store them as the pixels of discrete images. The main concern is whether and how th ...

EPFL2016

MATHICSE Technical Report : Discrete least-squares approximations over optimized downward closed polynomial spaces in arbitrary dimension

Fabio Nobile, Giovanni Migliorati

We analyze the accuracy of the discrete least-squares approximation of a function u in multivariate polynomial spaces

P_\Lambda := span\{y \mapsto y^\nu | \nu \in \Lambda\}

with

\Lambda\subset N_0^d

over the domain

\Gamma := [-1,1]^d

, based on the sa ...

MATHICSE2015

Random sampling of bandlimited signals on graphs

Pierre Vandergheynst, Rémi Gribonval, Gilles Puy, Nicolas Tremblay

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, \ie, independent of the graph structure, and its perform ...

2015

Dynamic Partitioned Sampling For Tracking With Discriminative Features

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Sampling and Exact Reconstruction of Pulses with Variable Width

On the performance of random reshuffling in stochastic learning

Learning-based subsampling

Extracting the interfacial free energy and anisotropy from a smooth fluctuating dividing surface

MATHICSE Technical Report : Multilevel ensemble Kalman filtering for spatio-temporal processes

MULTILEVEL ENSEMBLE KALMAN FILTERING FOR SPATIO-TEMPORAL PROCESSES

Development of the Geographical Proportional-to-size Street-Intercept Sampling (GPSIS) method for recruiting urban nightlife-goers in an entire city

Shapes from Pixels

MATHICSE Technical Report : Discrete least-squares approximations over optimized downward closed polynomial spaces in arbitrary dimension

Random sampling of bandlimited signals on graphs

Learning-based subsampling

On the performance of random reshuffling in stochastic learning

Sampling and Exact Reconstruction of Pulses with Variable Width

Development of the Geographical Proportional-to-size Street-Intercept Sampling (GPSIS) method for recruiting urban nightlife-goers in an entire city

MATHICSE Technical Report : Multilevel ensemble Kalman filtering for spatio-temporal processes

Shapes from Pixels

Random sampling of bandlimited signals on graphs

MULTILEVEL ENSEMBLE KALMAN FILTERING FOR SPATIO-TEMPORAL PROCESSES

MATHICSE Technical Report : Discrete least-squares approximations over optimized downward closed polynomial spaces in arbitrary dimension

Extracting the interfacial free energy and anisotropy from a smooth fluctuating dividing surface