Machine learning and integrative analysis of biomedical big data
Recent developments in high-throughput technologies have accelerated the accumulation
of massive amounts of omics data from multiple sources: genome, epigenome …
of massive amounts of omics data from multiple sources: genome, epigenome …
Towards effective network intrusion detection: from concept to creation on Azure cloud
Network Intrusion Detection is one of the most researched topics in the field of computer
security. Hacktivists use sophisticated tools to launch numerous attacks that hamper the …
security. Hacktivists use sophisticated tools to launch numerous attacks that hamper the …
Big data machine learning using apache spark MLlib
Artificial intelligence, and particularly machine learning, has been used in many ways by the
research community to turn a variety of diverse and even heterogeneous data sources into …
research community to turn a variety of diverse and even heterogeneous data sources into …
Removing backdoor-based watermarks in neural networks with limited data
X Liu, F Li, B Wen, Q Li - 2020 25th International Conference on …, 2021 - ieeexplore.ieee.org
Deep neural networks have been widely applied and achieved great success in various
fields. As training deep models usually consumes massive data and computational …
fields. As training deep models usually consumes massive data and computational …
Between access and privacy: challenges in sharing health data
Objective: To summarize notable research contributions published in 2017 on data sharing
and privacy issues in medical informatics. Methods: An extensive search of …
and privacy issues in medical informatics. Methods: An extensive search of …
Diabetes prediction using Shapley additive explanations and DSaaS over machine learning classifiers: a novel healthcare paradigm
Technologies like cloud computing, Artificial Intelligence (AI), and Machine intelligence
technologies must combine to accomplish computational intelligence. To deliberate the …
technologies must combine to accomplish computational intelligence. To deliberate the …
[PDF][PDF] Gateways to Artificial Intelligence: Developing a Taxonomy for AI Service Platforms.
F Geske, P Hofmann, L Lämmermann, V Schlatt… - ECIS, 2021 - researchgate.net
Artificial Intelligence (AI) carries the potential to drive innovation in many parts of today's
business environment. Instead of building AI capabilities in-house, some organizations turn …
business environment. Instead of building AI capabilities in-house, some organizations turn …
A two-stage big data analytics framework with real world applications using spark machine learning and long short-term memory network
Every day we experience unprecedented data growth from numerous sources, which
contribute to big data in terms of volume, velocity, and variability. These datasets again …
contribute to big data in terms of volume, velocity, and variability. These datasets again …
[PDF][PDF] Performance analysis of binary and multiclass models using azure machine learning.
S Rajagopal, KS Hareesha… - International Journal of …, 2020 - academia.edu
Network data is expanding and that too at an alarming rate. Besides, the sophisticated attack
tools used by hackers lead to capricious cyber threat landscape. Traditional models …
tools used by hackers lead to capricious cyber threat landscape. Traditional models …
REDsec: Running encrypted discretized neural networks in seconds
Abstract Machine learning as a service (MLaaS) has risen to become a prominent
technology due to the large development time, amount of data, hardware costs, and level of …
technology due to the large development time, amount of data, hardware costs, and level of …