Zobrazeno 1 - 10
of 811
pro vyhledávání: '"Aravkin, A."'
Autor:
Ducellier, Ariane, Hsu, Alexander, Kendrick, Parkes, Gustafson, Bill, Dwyer-Lindgren, Laura, Murray, Christopher, Zheng, Peng, Aravkin, Aleksandr
We consider statistical inference problems under uncertain equality constraints, and provide asymptotically valid uncertainty estimates for inferred parameters. The proposed approach leverages the implicit function theorem and primal-dual optimality
Externí odkaz:
http://arxiv.org/abs/2407.20520
Black-box optimization is ubiquitous in machine learning, operations research and engineering simulation. Black-box optimization algorithms typically do not assume structural information about the objective function and thus must make use of stochast
Externí odkaz:
http://arxiv.org/abs/2407.13576
Determining gene regulatory network (GRN) structure is a central problem in biology, with a variety of inference methods available for different types of data. For a widely prevalent and challenging use case, namely single-cell gene expression data m
Externí odkaz:
http://arxiv.org/abs/2407.00754
Identifying Ordinary Differential Equations (ODEs) from measurement data requires both fitting the dynamics and assimilating, either implicitly or explicitly, the measurement data. The Sparse Identification of Nonlinear Dynamics (SINDy) method involv
Externí odkaz:
http://arxiv.org/abs/2405.03154
Meta-analysis allows rigorous aggregation of estimates and uncertainty across multiple studies. When a given study reports multiple estimates, such as log odds ratios (ORs) or log relative risks (RRs) across exposure groups, accounting for within-stu
Externí odkaz:
http://arxiv.org/abs/2404.11678
Autor:
Zheng, Peng, Worku, Nahom, Bannick, Marlena, Dielemann, Joseph, Weaver, Marcia, Murray, Christopher, Aravkin, Aleksandr
Benchmarking tools, including stochastic frontier analysis (SFA), data envelopment analysis (DEA), and its stochastic extension (StoNED) are core tools in economics used to estimate an efficiency envelope and production inefficiencies from data. The
Externí odkaz:
http://arxiv.org/abs/2404.04301
Efficient representations of data are essential for processing, exploration, and human understanding, and Principal Component Analysis (PCA) is one of the most common dimensionality reduction techniques used for the analysis of large, multivariate da
Externí odkaz:
http://arxiv.org/abs/2311.01826
Autor:
Pillonetto, Gianluigi, Aravkin, Aleksandr, Gedon, Daniel, Ljung, Lennart, Ribeiro, Antônio H., Schön, Thomas B.
Deep learning is a topic of considerable current interest. The availability of massive data collections and powerful software resources has led to an impressive amount of results in many application areas that reveal essential but hidden properties o
Externí odkaz:
http://arxiv.org/abs/2301.12832
We develop a Levenberg-Marquardt method for minimizing the sum of a smooth nonlinear least-squar es term $f(x) = \tfrac{1}{2} \|F(x)\|_2^2$ and a nonsmooth term $h$. Both $f$ and $h$ may be nonconvex. Steps are computed by minimizing the sum of a reg
Externí odkaz:
http://arxiv.org/abs/2301.02347
Spatiotemporal data is increasingly available due to emerging sensor and data acquisition technologies that track moving objects. Spatiotemporal clustering addresses the need to efficiently discover patterns and trends in moving object behavior witho
Externí odkaz:
http://arxiv.org/abs/2211.05337