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Extracting Data at Scale: Machine learning at the Natural History Museum

Ben Scott, Laurence Livermore
2021 Biodiversity Information Science and Standards  
Machine learning applications can deliver a step-change in our activities' scope, scale, and speed (Borsch et al. 2020).  ...  This presentation will give an overview of these projects, and our future plans for using ML to extract data at scale within the Natural History Museum.  ...  Machine learning applications can deliver a step-change in our activities' scope, scale, and speed (Borsch et al. 2020 ).  ... 
doi:10.3897/biss.5.74031 fatcat:o4xkzf4ftjg4pcklu3g7jilfdi

Deep Learning Frameworks In High Performance Computing Environments

Dr. Ganapathi Pulipaka
2018 Zenodo  
and large-scale data.  ...  However, there is no integrated research that offers insights into the deep learning frameworks that crunch the big data at scale.  ... 
doi:10.5281/zenodo.1186971 fatcat:eggksvlahzfd3inqj3zwats3yi

Accelerating skills development in Data science and AI at scale

Titus Tang
2020 Zenodo  
At the Monash Data Science and AI platform, we believe that upskilling our research community and building a workforce with data science skills are key to accelerating the application of data science in  ...  In this talk, we will discuss the principles and purpose of establishing collaborative models to accelerate skills development at scale.  ...  researchers with large and complex datasets to apply data science, Machine Learning and AI to their research • Underpin the Monash Data Futures Institute, translating discoveries into life-changing  ... 
doi:10.5281/zenodo.4287745 fatcat:k22bsbadlffqlhiwj3fiuaowwu

Integrating machine learning and multiscale modeling—perspectives, challenges, and opportunities in the biological, biomedical, and behavioral sciences

Mark Alber, Adrian Buganza Tepole, William R. Cannon, Suvranu De, Salvador Dura-Bernal, Krishna Garikipati, George Karniadakis, William W. Lytton, Paris Perdikaris, Linda Petzold, Ellen Kuhl
2019 npj Digital Medicine  
The recent rise of machine learning as a powerful technique to integrate multimodality, multifidelity data, and reveal correlations between intertwined phenomena presents a special opportunity in this  ...  Fueled by breakthrough technology developments, the biological, biomedical, and behavioral sciences are now collecting more data than ever before.  ...  Theory-driven machine learning can yield data-efficient workflows for predictive modeling by synthesizing prior knowledge and multimodality data at different scales.  ... 
doi:10.1038/s41746-019-0193-y pmid:31799423 pmcid:PMC6877584 fatcat:uhgdhq7rjffqnboydb3e6d2tuu

Second International Workshop on Data-Centric Dependability and Security (DCDS)

Ibéria Medeiros, Ilir Gashi, Michael Kamp, Pedro Ferreira
2020 Dependable Systems and Networks  
This calls for solutions combining the latest advances in areas such as large-scale data processing, data science, visualization and machine and statistical learning.  ...  It aims to discuss novel approaches for processing and analysing data generated by the systems as well as information gathered from open sources, leveraging from data science, machine and statistical learning  ...  This calls for solutions combining the latest advances in areas such as large-scale data processing, data science, visualization and machine and statistical learning.  ... 
doi:10.1109/dsn-w50199.2020.00007 dblp:conf/dsn/MedeirosGKF20 fatcat:rmvpyxjgxfahzesaxqnhzos4b4

How the Public Clouds are Innovating on AI

Mohamed El-Hadi
2022 Compunet ( The Egyptian Information Journal )  
to develop, test, and deploy machine learning models on their clouds.  ...  How the Public Clouds are Innovating on AI Thinkstock The three big cloud providers, specifically Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP), want developers and data scientists  ...  Battle of the AI services Most data science teams won't be developing massive-scale AI but do want to create and configure advanced machine learning models.  ... 
doi:10.21608/jstc.2022.252012 fatcat:t7twjdwdfbhs5ktvzpywmmioga

Big Data Analytics using Meta Machine Learning
English

Bharati Suvalka, Sarika kandelwal, Sidharth Singh Sisodia
2014 International Journal of Innovative Research in Science Engineering and Technology  
As "Big Data" grows bigger at a rapid speed, Machine Learning (MACHINE LEARNING) techniques have come to play a vital role in automatic data processing and analytics across a wide spectrum of application  ...  We wish to refer to this science as "Meta-Machine Learning" (MMACHINE LEARNING).  ...  One idea that can be explore is the primary mapping between large-scale data streams and learning algorithms.  ... 
doi:10.15680/ijirset.2014.0308072 fatcat:3qwqpolrerf6jj5c77yqpwdoee

Machine Learning and Ecosystem Informatics: Challenges and Opportunities [chapter]

Thomas G. Dietterich
2009 Lecture Notes in Computer Science  
This talk will discuss the ways in which machine learning-in combination with novel sensors-can help transform the ecosystem sciences from small-scale hypothesis-driven science to global-scale data-driven  ...  The talk will also discuss the recent development of The Evidence Tree Methodology for complex machine learning applications.  ...  At the other extreme-which we might call "science-in-the-large"-automated instruments collect massive amounts of observational data, which are then analyzed via machine learning and data mining algorithms  ... 
doi:10.1007/978-3-642-05224-8_1 fatcat:4z7jjud7pjavrnee33ctkobgvq

Artificial Intelligence Integration with Nanotechnology

Farahnaz Behgounia, Bahman Zohuri
2020 Nanotechnology & Applications  
In this short communication, we present such innovative and dynamic sites utilizing artificial intelligence and its sub-sets of machine learning driven by deep learning in Nanotechnology.  ...  AI has predictive power based on its data analytic functionality and some levels of autonomous learning, which its raw ingredient is just the massive sheer volume of data.  ...  data at the speed of your computer Central Processing Unit (CPU), digital at scale and speed (i.e., nanotechnology), optimizing your business.  ... 
doi:10.33425/2639-9466.1025 fatcat:nqw52lett5d4hbdfiu7yam46ce

Third International Workshop on Data-Centric Dependability and Security (DCDS)

Iberia Medeiros, Ilir Gashi, Michael Kamp, Pedro Ferreira
2021 2021 51st Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshops (DSN-W)  
This calls for solutions combining the latest advances in areas such as large-scale data processing, data science, visualization and machine and statistical learning.  ...  It aims to discuss novel approaches for processing and analysing data generated by the systems and information gathered from open sources, leveraging from data science, machine and statistical learning  ...  This calls for solutions combining the latest advances in areas such as large-scale data processing, data science, visualization and machine and statistical learning.  ... 
doi:10.1109/dsn-w52860.2021.00006 fatcat:ktd7ecfssfftvcbb7feqxnrbja

Message from the DCDS 2019 Organizers

2019 2019 49th Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshops (DSN-W)  
This calls for solutions combining the latest advances in areas such as large-scale data processing, data science, visualization and machine and statistical learning.  ...  It aims to discuss novel approaches for processing and analysing data generated by the systems as well as information gathered from open sources, leveraging from data science, machine and statistical learning  ...  Moreover, we would like to thank the organizers of the DSN conference for their help and support of the DCDS workshop and the community for their valued contributions to the workshop.  ... 
doi:10.1109/dsn-w.2019.00006 fatcat:hlktiqqo55dvdkdifj7bqfqplu

CANFAR+Skytree: A Cloud Computing and Data Mining System for Astronomy [article]

Nicholas M. Ball
2013 arXiv   pre-print
Because Skytree scales to large data in linear runtime, this allows the full sophistication of the huge fields of data mining and machine learning to be applied to the hundreds of millions of objects that  ...  At the Canadian Astronomy Data Centre, we have combined our cloud computing system, CANFAR, with the world's most advanced machine learning software, Skytree, to create the world's first cloud computing  ...  Gray and M. Hack for their contributions to this work.  ... 
arXiv:1312.3996v1 fatcat:mhm6ffqi4vhkhpekhz5ujdcddu

Scientific Machine Learning Benchmarks [article]

Jeyan Thiyagalingam, Mallikarjun Shankar, Geoffrey Fox, Tony Hey
2021 arXiv   pre-print
With a new generation of experimental facilities, the rate of data generation and the scale of data volumes will increasingly require the use of more automated data analysis.  ...  In the context of science, scientific machine learning focuses on training machines to identify patterns, trends, and anomalies to extract meaningful scientific insights from such datasets.  ...  Acknowledgements: We would like to thank Samuel Jackson, Kuangdai Leng, Keith Butler and Juri Papay from the Scientific Machine Learning Research Group at the Rutherford Appleton Laboratory, Junqi Yin  ... 
arXiv:2110.12773v1 fatcat:xrrwsb25jva5nab2t5qxgqtj6a

Automated Data Analysis Strategy for Synchrotron Experiments

Lifen Yan
2017 International Journal of Applied Science - Research and Review  
and time-scales.  ...  And there are lots of existing data which can be used to train machine based systems. In all, Machine Learning has the potential to become an important component of materials research.  ... 
doi:10.21767/2394-9988.100057 fatcat:vwgxjynwk5fyjjsksiqannsjdi

CONVERGENCE OF HPC AND AI: TWO DIRECTIONS OF CONNECTION

Nigar Ismayilova, Elviz Ismayilov
2018 Azerbaijan Journal of High Performance Computing  
The findings from the literature review illustrate how these two main fields of science and information technologies can be converged together for the achievement of the goals in designing and developing  ...  Reviewing of large-scale data, mining of significant and unknown knowledge and facts from the enormous amount of information are the challenging problems of machine learning and big data.  ...  Applications of machine learning algorithms in big data Big data analytics, extraction of useful knowledge from the massive scale of information, causal inference through the texts, text summarization,  ... 
doi:10.32010/26166127.2018.1.2.179.184 fatcat:vhxbfrgtcfhi3m2xjqdewtu4aq
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