Assessing toxic impacts on aquatic ecosystems in life cycle assessment (LCA)
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Streams are significant sources of CO2 to the atmosphere. Estimates of CO2 evasion fluxes (fCO2) from streams typically relate to the free flowing water but exclude geomorphological structures within the stream corridor. We found that gravel bars (GBs) are ...
The high energy physics unfolding problem is an important statistical inverse problem in data analysis at the Large Hadron Collider (LHC) at CERN. The goal of unfolding is to make nonparametric inferences about a particle spectrum from measurements smeared ...
Query optimizers depend heavily on statistics representing column distributions to create efficient query plans. In many cases, though, statistics are outdated or non-existent, and the process of refreshing statistics is very expensive, especially for ad-h ...
Compressive sensing generally relies on the L2-norm for data fidelity, whereas in many applications robust estimators are needed. Among the scenarios in which robust performance is required, applications where the sampling process is performed in the prese ...
In general, reliable studies are well designed and well performed, and enough details on study design and performance are reported to assess the study. For hazard and risk assessment in various legal frameworks, many different types of ecotoxicity studies ...
We consider the high energy physics unfolding problem where the goal is to estimate the spectrum of elementary particles given observations distorted by the limited resolution of a particle detector. This important statistical inverse problem arising in da ...
In Part II of this paper, also in this issue, we carried out a detailed mean-square-error analysis of the performance of asynchronous adaptation and learning over networks under a fairly general model for asynchronous events including random topologies, ra ...
Institute of Electrical and Electronics Engineers2015
Solving a linear inverse problem may include difficulties such as the presence of outliers and a mixing matrix with a large condition number. In such cases a regularized robust estimator is needed. We propose a new tau-type regularized robust estimator tha ...
This paper proposes a tradeoff between computational time, sample complexity, and statistical accuracy that applies to statistical estimators based on convex optimization. When we have a large amount of data, we can exploit excess samples to decrease stati ...
This thesis studies statistical inference in the high energy physics unfolding problem, which is an ill-posed inverse problem arising in data analysis at the Large Hadron Collider (LHC) at CERN. Any measurement made at the LHC is smeared by the finite reso ...