In modern statistical and machine learning applications, however, computer scientists, statisticians, and analysts have a variety of additional criteria they must balance: estimators must be efficiently computable, data providers may wish to maintain anonymity, large datasets must be stored and accessed.
Since it is hard to maintain the large dataset for real applications, the latest algorithms for human action recognition tend to be template-based.
However, industry, science, and commerce fields often need to analyze very large datasets maintained over geographically distributed sites by using the computational power of distributed systems.
A clustering approach should however also maintain cluster efficiency levels when large datasets are involved by considering inter and intra-clustering distances between data objects in a dataset.
Hazy - An AI spin-out from UCL, Hazy is a platform that helps businesses identify and anonymise personal data in large datasets whilst maintaining its utility, enabling Hazy's customers to remain GDPR compliant.
Extensive experiments over real-world datasets are conducted to demonstrate that the proposed protocols maintain high usability and scale well to large datasets.
SPARK overcomes both limitations by performing in-memory caching for each executor, which eliminates the disk IO bottleneck on smaller datasets, while maintaining scalability to larger datasets by spilling data that exceeds memory availability to disk.
Additionally, the data structures within NAViGaTOR were designed to maintain a small memory footprint in order to provide greater scalability for large datasets.
The recently proposed predictive process, motivated by kriging ideas, aims to maintain the richness of desired hierarchical spatial modeling specifications in the presence of large datasets.
This poses problems for data security and confidentiality, is unfeasible for the large datasets typically generated in high-throughput multiplex sequencing projects and excludes the use of privately maintained MLST databases.
