Publications related to Random sampling of bandlimited signals on graphs

Sampling at unknown locations, with an application in surface retrieval

Martin Vetterli, Benjamin Bejar Haro, Adam James Scholefield, Michalina Wanda Pacholska

We consider the problem of sampling at unknown locations. We prove that, in this setting, if we take arbitrarily many samples of a polynomial or real bandlimited signal, it is possible to find another function in the same class, arbitrarily far away from t ...

2017

Lower Bounds on Active Learning for Graphical Model Selection

Volkan Cevher, Jonathan Mark Scarlett

We consider the problem of estimating the underlying graph associated with a Markov random field, with the added twist that the decoding algorithm can iteratively choose which subsets of nodes to sample based on the previous samples, resulting in an active ...

2017

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 s ...

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

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

Multilevel weighted least squares polynomial approximation

Fabio Nobile

Weighted least squares polynomial approximation uses random samples to determine projections of functions onto spaces of polynomials. It has been shown that, using an optimal distribution of sample locations, the number of samples required to achieve quasi ...

2017

Gauging the highs: design and realization of a water sample campaign during high and low streamflow

How does the streamwater quality change during storm events, and how to characterize it? The purpose of this study is to investigate the evolution of major ions in streamwater from base ow to storm ux. Regular manual sampling and automated sampling campaig ...

2017

MATHICSE Technical Report : Multilevel weighted least squares polynomial approximation

Fabio Nobile

Weighted least squares polynomial approximation uses random samples to determine projections of functions onto spaces of polynomials. It has been shown that, using an optimal distribution of sample locations, the number of samples required to achieve quasi ...

MATHICSE2017

Just Sort It! A Simple and Effective Approach to Active Preference Learning

Matthias Grossglauser, Lucas Maystre

We address the problem of learning a ranking by using adaptively chosen pairwise comparisons. Our goal is to recover the ranking accurately but to sample the comparisons sparingly. If all comparison outcomes are consistent with the ranking, the optimal sol ...

2017

Effect-based tools for monitoring estrogenic mixtures: Evaluation of five in vitro bioassays

In vitro estrogen receptor transactivation assays (ERTAs) are increasingly used to measure the overall estrogenic activity of environmental water samples, which may serve as an indicator of exposure of fish or other aquatic organisms to (xeno)estrogens. An ...

Pergamon-Elsevier Science Ltd2017

Random sampling of bandlimited signals on graphs

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Sampling at unknown locations, with an application in surface retrieval

Lower Bounds on Active Learning for Graphical Model Selection

Discrete least-squares approximations over optimized downward closed polynomial spaces in arbitrary dimension

Quasi-random numbers for copula models

On the performance of random reshuffling in stochastic learning

Multilevel weighted least squares polynomial approximation

Gauging the highs: design and realization of a water sample campaign during high and low streamflow

MATHICSE Technical Report : Multilevel weighted least squares polynomial approximation

Just Sort It! A Simple and Effective Approach to Active Preference Learning

Effect-based tools for monitoring estrogenic mixtures: Evaluation of five in vitro bioassays

Quasi-random numbers for copula models

Lower Bounds on Active Learning for Graphical Model Selection

Gauging the highs: design and realization of a water sample campaign during high and low streamflow

Sampling at unknown locations, with an application in surface retrieval

Multilevel weighted least squares polynomial approximation

Effect-based tools for monitoring estrogenic mixtures: Evaluation of five in vitro bioassays

Discrete least-squares approximations over optimized downward closed polynomial spaces in arbitrary dimension

On the performance of random reshuffling in stochastic learning

Just Sort It! A Simple and Effective Approach to Active Preference Learning

MATHICSE Technical Report : Multilevel weighted least squares polynomial approximation