Company Filing History:
Years Active: 2016
Title: Warren Sarle: Innovator in Data Analysis and Clustering Techniques
Introduction
Warren Sarle is a notable inventor based in Gainesville, FL (US). He has made significant contributions to the field of data analysis and clustering techniques. With a total of 2 patents, his work focuses on enhancing the efficiency and effectiveness of data processing methods.
Latest Patents
Warren Sarle's latest patents include innovative systems and methods for providing a unified variable selection approach based on variance preservation. This patent describes a method, system, and computer-program product for parallelized feature selection. The approach allows for accessing a first set of features characterized by a variance measure, determining components of a covariance matrix, and selecting multiple features based on these components. The selection process utilizes a greedy search performed through parallelized computation.
Another significant patent is related to the estimation of the number of clusters in a dataset. This method involves determining centroid locations for a defined number of clusters using a clustering algorithm. It also includes creating a reference distribution of data points within the defined boundaries of the clusters. By computing a gap statistic based on residual sums of squares, the method iteratively estimates the best number of clusters for the received data.
Career Highlights
Warren Sarle is currently employed at SAS Institute Inc., where he continues to develop innovative solutions in data analysis. His expertise in clustering and feature selection has positioned him as a valuable asset in the field.
Collaborations
Warren has collaborated with notable colleagues such as Patrick Hall and Ilknur Kaynar Kabul. Their combined efforts contribute to advancing research and development in data analysis techniques.
Conclusion
Warren Sarle's contributions to the field of data analysis and clustering techniques are noteworthy. His innovative patents and collaborative efforts reflect his commitment to enhancing data processing methodologies.
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