Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 13 of 13 for “"mean estimation"”.
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Variance reduction for Poisson and Markov jump processes
… reduction algorithms for the simulation and estimation of stochastic dynamic models. It provides particular application to particle dynamics models including an emissions process and radioactive decay. These algorithms apply several variance reduction techniques to the generation of Poisson …
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Principled approaches to robust machine learning and beyond
… similarly inspired, algorithmic paradigms for estimation in high dimensions in the presence of a small number of adversarially added data points. Both algorithms are the first efficient algorithms which achieve (nearly) optimal error bounds for a number fundamental statistical tasks such as …
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Topics In Differentially Private Statistical Inference
… privacy and statistical accuracy in parameter estimation problems. We understand the privacy-accuracy trade-off by finding the best achievable accuracy of any differentially private algorithm, also known as the "privacy-constrained minimax risk", in a series of statistical problems: Gaussian …
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Cluster Analysis in High Dimensions: Robustness, Privacy, and Beyond
… data into closely related groups, such as in k-means clustering and learning mixture models. However, one sometimes overlooked part of cluster analysis is analyzing data from a single cluster: this encompasses problems such as mean estimation and covariance estimation, which correspond to …
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A spectral approach for noninvasive estimation of intracranial pressure
… (CBFV) measurements. To support such ICP estimation, we developed a data acquisition system to archive high quality, high resolution waveforms from various bedside monitoring devices along a common time axis and deployed the system at the neurocritical care units at Boston Medical Center. …
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Essays in Economic *Growth and Asset Pricing
… in previous studies. Using semi-parametric estimation procedures we find ample evidence of pairwise convergence among 15 OECD countries. This result is contrary to the literature that uses unit roots and cointegration tests to analyze income convergence. In chapter 3, we propose a novel …
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Computational Advancements for Solving Large-scale Inverse Problems
… methods have been critical in obtaining stable estimations by applying prior information of unknowns via Bayesian inference. However, by combining iterative projection methods and variational regularization methods, hybrid projection approaches, in particular generalized hybrid methods, create a …
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An Endogenous Metric for the Perception of Short Temporal Intervals
… and forty-one second periods using an operative estimation technique, while concomitantly recording trials. There were twenty trials at each period for both a filled and unfilled manipulation. In the placebo condition a heating helmet was worn but not activated, while the control condition was …
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Automated and Provable Privatization for Black-Box Processing
… characterize privacy risk through a statistical mean estimation. Provided sufficient sampling, one can approach this objective risk bound arbitrarily closely, which thus leads to a high confidence proof. The established theory also connects algorithmic stability and generalization error, …
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Reducibility and Statistical-Computational Gaps from Secret Leakage
… range of problems including robust sparse mean estimation, mixtures of sparse linear regressions, robust sparse linear regression, tensor PCA, variants of dense 𝑘-block stochastic block models, negatively correlated sparse PCA, semirandom planted dense subgraph, detection in hidden …
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Modeling and estimation for non-invasive monitoring of intracranial pressure and cerebrovascular autoregulation
… Pooling all independent estimates resulted in a mean estimation error (bias) of less than 2 mmHg and a standard deviation of error of about 8 mmHg. We also suggest how variations in estimated cerebrovascular resistance and compliance in response to variations in cerebral perfusion pressure may be …
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Efficient algorithms for distributed learning, optimization and belief systems over networks
… we present a generic distributed parameter estimation algorithm for observational models belonging to the exponential family of distributions. We further extend the distributed mean estimation from Gaussian observations to time-varying directed networks. The graph-theoretical analysis of …
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Statistical models for estimating the intake of nutrients and foods from complex survey data
… measurement error, to be accounted for in the estimation procedure for correct inferences. Thirdly, the complex sample design needs to be incorporated into the estimation procedure to allow extrapolation of results into the target population. This thesis aims to develop novel statistical …