Company Filing History:
Years Active: 2015-2020
Title: Udo Sglavo: Innovator in Machine Learning and Time-Series Forecasting
Introduction
Udo Sglavo is a prominent inventor based in Raleigh, NC, known for his contributions to machine learning and time-series data forecasting. With a total of seven patents to his name, Sglavo has made significant strides in developing innovative solutions that enhance predictive modeling and data analysis.
Latest Patents
Sglavo's latest patents include a "System for automatic, simultaneous feature selection and hyperparameter tuning for a machine learning model." This invention involves a computing device that selects a feature set and hyperparameters to predict values for characteristics in a scoring dataset. The process includes determining the number of training model iterations and selecting unique evaluation pairs for each iteration. Each trained machine learning model is validated to compute a performance measure value, leading to the selection of a final feature set and hyperparameter configuration based on these values.
Another notable patent is the "Pipeline system for time-series data forecasting." This invention utilizes a distributed computing environment to generate a pipeline for forecasting time series. The pipeline represents a sequence of operations that process the time series to produce forecasts. It includes model strategy operations to apply various strategies and determine error distributions, ultimately identifying a champion model strategy based on these distributions.
Career Highlights
Udo Sglavo is currently employed at SAS Institute Inc., a leading analytics software company. His work focuses on advancing machine learning techniques and improving forecasting methodologies. His innovative approaches have contributed to the development of more efficient and accurate predictive models.
Collaborations
Sglavo has collaborated with notable colleagues, including Michael James Leonard and Jerzy Michal Brzezicki. These partnerships have fostered a collaborative environment that encourages the exchange of ideas and the development of cutting-edge technologies.
Conclusion
Udo Sglavo's contributions to the fields of machine learning and time-series forecasting exemplify his innovative spirit and dedication to advancing technology. His patents reflect a commitment to improving predictive modeling, making significant impacts in the industry.