4 citations · 4 across the 5 of their papers we have counts for
5 papers
Efficient subsampling for high-dimensional data
Vasilis Chasiotis, Lin Wang, Dimitris Karlis
In the field of big data analytics, the search for efficient subdata selection methods that enable robust statistical inferences with minimal computational resources is of high imp…
On the estimation of complex statistics combining different surveys
Vasilis Chasiotis, Dimitris Karlis
The importance of exploring a potential integration among surveys has been acknowledged in order to enhance effectiveness and minimize expenses. In this work, we employ the alignme…
Optimal subdata selection for linear model selection
Vasilis Chasiotis, Dimitris Karlis
If the assumed model does not accurately capture the underlying structure of the data, a statistical method is likely to yield sub-optimal results, and so model selection is crucia…
On the selection of optimal subdata for big data regression based on leverage scores
Vasilis Chasiotis, Dimitris Karlis
The demand of computational resources for the modeling process increases as the scale of the datasets does, since traditional approaches for regression involve inverting huge data…
Subdata selection for big data regression: an improved approach
Vasilis Chasiotis, Dimitris Karlis
In the big data era researchers face a series of problems. Even standard approaches/methodologies, like linear regression, can be difficult or problematic with huge volumes of data…