Matthias Seeger

Title: Matthias Seeger: Innovator in Machine Learning and Time Series Forecasting

Introduction

Matthias Seeger is a prominent inventor based in Berlin, Germany. He has made significant contributions to the fields of machine learning and artificial intelligence. With a total of 3 patents, his work focuses on optimizing hyperparameters and developing advanced forecasting models.

Latest Patents

One of Matthias Seeger's latest patents is titled "Hyperparameter optimization with operational constraints." This innovation involves optimizing hyperparameters for tuning a machine learning system using Bayesian optimization with constraints. The process includes initializing probabilistic models for the machine learning system and constraint functions, iteratively identifying hyperparameter values, and training the system to determine accuracy and constraint metrics.

Another notable patent is "Artificial intelligence system combining state space models and neural networks for time series forecasting." This composite model integrates a neural network sub-model with state space sub-models corresponding to individual time series. During training, the neural network's output is utilized to determine parameters of the state space sub-models, and a loss function is computed based on the time series values and probabilistic outputs.

Career Highlights

Matthias Seeger is currently employed at Amazon Technologies, Inc., where he continues to innovate in the realm of artificial intelligence and machine learning. His work has garnered attention for its practical applications and contributions to the field.

Collaborations

Throughout his career, Matthias has collaborated with notable colleagues, including Jan Alexander Gasthaus and Gregory Michael Duncan. These partnerships have further enriched his research and development efforts.

Conclusion

Matthias Seeger stands out as a key figure in the innovation landscape of machine learning and artificial intelligence. His patents reflect a commitment to advancing technology and improving forecasting methods. His contributions are likely to have a lasting impact on the industry.