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Increasingly, uncertainties are explicitly considered for important engineering tasks. Often, little case-specific information is available for characterizing these uncertainties. Uniform distributions are an easy way to describe errors in absence of more ...
In this work, we investigate the relationship between continuous-time autoregressive (AR) models and their sampled version. We consider uniform sampling and derive criteria for uniquely determining the continuous-time parameters from sampled data; the mode ...
We consider the task of estimating an operator from sampled data. The operator, which is described by a rational transfer function, is applied to continuous-time white noise and the resulting continuous-time process is sampled uniformly. The main question ...
This paper investigates age mixing processes arising in advection-dispersion models, where large-scale travel and residence time distributions can be explicitly calculated based on the underlying velocity field. In particular, we analyze spatially integrat ...
The efficiency of the simplest isomeric search procedure consisting in random generation of sets of atomic coordinates followed by density functional theory geometry optimization is tested on the silicon cluster series (Si-5-10,Si-15,Si-20). Criteria such ...
To improve visual tracking, a large number of papers study more powerful features, or better cue fusion mechanisms, such as adaptation or contextual models. A complementary approach consists of improving the track management, that is, deciding when to add ...
We study mechanical reinforcement in a widely used epoxy matrix with the addition of graphene nanoplatelets (GnPs) and various mixture ratios of carbon nanotubes (CNTs) with GnPs. Two different dimensions of GnPs were used with flake sizes of 5 mu m and 25 ...
Using multiple families of image features is a very efficient strategy to improve performance in object detection or recognition. However, such a strategy induces multiple challenges for machine learning methods, both from a computational and a statistical ...
The ever-growing need for gene-expression data analysis motivates studies in sample generation due to the lack of enough gene-expression data. It is common that there are thousands of genes but only tens or rarely hundreds of samples available. In this pap ...
We study the problem of learning ridge functions of the form f(x) = g(aT x), x ∈ ℝd, from random samples. Assuming g to be a twice continuously differentiable function, we leverage techniques from low rank matrix recovery literature to derive a uniform app ...
