Results 1 to 10 of about 2,162,093 (215)
Data-Driven Polyoxometalate Chemistry. [PDF]
ChemistryAbstractPolyoxometalates (POMs) are nanoscale, structurally versatile metal–oxo clusters with emerging applications in sustainability, energy, nanoelectronics, and life science technologies. Owing to their structural complexity, some all‐inorganic POMs are often perceived as serendipitous outcomes from self‐assembly processes, which poses challenges ...
Kondinski A +4 more
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PLOS ONE, 2020 Biological network alignment (NA) aims to find a node mapping between species' molecular networks that uncovers similar network regions, thus allowing for transfer of functional knowledge between the aligned nodes.
Gu, Shawn, Milenkovic, Tijana
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Data-Driven Robust Optimization [PDF]
Mathematical Programming, 2014 The last decade witnessed an explosion in the availability of data for operations research applications. Motivated by this growing availability, we propose a novel schema for utilizing data to design uncertainty sets for robust optimization using ...
Bertsimas, Dimitris +2 more
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Data-Driven Computing in Dynamics [PDF]
International Journal for Numerical Methods in Engineering, 2017 We formulate extensions to Data Driven Computing for both distance minimizing and entropy maximizing schemes to incorporate time integration. Previous works focused on formulating both types of solvers in the presence of static equilibrium constraints ...
Kirchdoerfer, Trenton, Ortiz, Michael
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Data-driven Stellar Models [PDF]
The Astrophysical Journal, 2021 Abstract We developed a data-driven model to map stellar parameters (T eff, , and ) accurately and precisely to broadband stellar photometry.
Gregory M. Green +9 more
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Data-Driven Nonsmooth Optimization [PDF]
SIAM Journal on Optimization, 2020 In this work, we consider methods for solving large-scale optimization problems with a possibly nonsmooth objective function. The key idea is to first specify a class of optimization algorithms using a generic iterative scheme involving only linear operations and applications of proximal operators.
Sebastian Banert +4 more
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Data-Driven Predictive Maintenance
IEEE Intelligent Systems, 2022 With the growth of 5G networks, the Internet-of-Things is becoming a reality. The advances in networking, machine learning, data analytics, and robotics largely improve industrial processes. Industry 4.0 is a term for the fourth industrial revolution: the digitization and automation of manufacturing [1].
Joao Gama, Rita P. Ribeiro, Bruno Veloso
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Data Driven Discovery in Astrophysics [PDF]
, 2014 We review some aspects of the current state of data-intensive astronomy, its methods, and some outstanding data analysis challenges. Astronomy is at the forefront of "big data" science, with exponentially growing data volumes and data rates, and an ever ...
Brescia, M. +4 more
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EMBO reports, 2012 Omics technologies and the large data sets they produce do not undermine hypothesis‐driven research. Rather, they help scientists formulate better and more relevant hypotheses to be put to the test.
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Data-driven trajectory smoothing [PDF]
Proceedings of the 19th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, 2011 Motivated by the increasing availability of large collections of noisy GPS traces, we present a new data-driven framework for smoothing trajectory data. The framework, which can be viewed of as a generalization of the classical moving average technique, naturally leads to efficient algorithms for various smoothing objectives.
Chazal, Frédéric +4 more
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