Results 31 to 40 of about 14,568,367 (342)
Gradient Amplification: An Efficient Way to Train Deep Neural Networks
Big Data Mining and Analytics, 2020 Improving performance of deep learning models and reducing their training times are ongoing challenges in deep neural networks. There are several approaches proposed to address these challenges, one of which is to increase the depth of the neural ...
Sunitha Basodi +3 more
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Survey on Data Analysis in Social Media: A Practical Application Aspect
Big Data Mining and Analytics, 2020 Social media has more than three billion users sharing events, comments, and feelings throughout the world. It serves as a critical information source with large volumes, high velocity, and a wide variety of data.
Qixuan Hou, Meng Han, Zhipeng Cai
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A Software Development Model for the Automatic Generation of Classes
CLEI Electronic Journal, 2018 In this paper it is presented a software development model based on transformations that allows to derive, in an automatic way, classes in object-oriented programming languages (Ada 95, C++, Eiffel and Java) starting from formal specifications.
Eugenio Scalise, Nancy Zambrano
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Blockchain Abstract Data Type [PDF]
The 31st ACM Symposium on Parallelism in Algorithms and Architectures, 2019 The presented work continues the line of recent distributed computing communityefforts dedicated to the theoretical aspects of blockchains. This paper is the rst tospecify blockchains as a composition of abstract data types all together with a hierarchyof consistency criteria that formally characterizes the histories admissible for distributedprograms ...
Anceaume, Emmanuelle +4 more
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Effective Variational Data Assimilation in Air-Pollution Prediction
Big Data Mining and Analytics, 2018 Numerical simulations are widely used as a predictive tool to better understand complex air flows and pollution transport on the scale of individual buildings, city blocks, and entire cities.
Rossella Arcucci +2 more
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Backscatter technologies and the future of Internet of Things: Challenges and opportunities
Intelligent and Converged Networks, 2020 Energy source and circuit cost are two critical challenges for the future development of the Internet of Things (IoT). Backscatter communications offer a potential solution to conveniently obtain power and reduce cost for sensors in IoT, and researchers ...
Chaochao Yao +4 more
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Model Error Correction in Data Assimilation by Integrating Neural Networks
Big Data Mining and Analytics, 2019 In this paper, we suggest a new methodology which combines Neural Networks (NN) into Data Assimilation (DA). Focusing on the structural model uncertainty, we propose a framework for integration NN with the physical models by DA algorithms, to improve ...
Jiangcheng Zhu +5 more
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2013 28th Annual ACM/IEEE Symposium on Logic in Computer Science, 2013 Data types are undergoing a major leap forward in their sophistication driven by a conjunction of i) theoretical advances in the foundations of data types, and ii) requirements of programmers for ever more control of the data structures they work with.
Ghani, Neil +3 more
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Towards an induction principle for nested data types [PDF]
arXiv, 2023 A well-known problem in the theory of dependent types is how to handle so-called nested data types. These data types are difficult to program and to reason about in total dependently typed languages such as Agda and Coq. In particular, it is not easy to derive a canonical induction principle for such types.
arxiv
Bayesian nonparametric models for spatially indexed data of mixed type [PDF]
, 2014 We develop Bayesian nonparametric models for spatially indexed data of mixed type. Our work is motivated by challenges that occur in environmental epidemiology, where the usual presence of several confounding variables that exhibit complex interactions ...
Best, Nicky +2 more
core +2 more sources