Mohammad Saad Abdul Karim Kayali

Title: Mohammad Saad Abdul Karim Kayali and Machine-Learning Configuration Portfolios.

Introduction

Mohammad Saad Abdul Karim Kayali is an inventor associated with Seattle, Washington, and Microsoft Technology Licensing, LLC. His patent work addresses efficient ways to select machine-learning model configurations for a range of tasks.

Latest Patents

Kayali is associated with 1 patent, titled “Generating a Configuration Portfolio Including a Set of Model Configurations.” The invention describes creating a compact portfolio of model configurations predicted to perform well across varied input tasks. It evaluates machine-learning models on training tasks and uses their accuracy to build a regret matrix. The system then selects configurations with lower regret, aiming to provide reasonable performance on new tasks while using fewer processing resources than conventional model-selection approaches.

Career Highlights

The available information connects Kayali’s patent activity with Microsoft Technology Licensing, LLC. His disclosed work focuses on model selection and resource-efficient machine-learning systems.

Collaborations

Kayali’s listed coworker is Chi Wang. The patent’s subject matter reflects work involving machine-learning models and methods for evaluating their performance across tasks.

Conclusion

Mohammad Saad Abdul Karim Kayali’s patent describes a practical approach to assembling a compact portfolio of machine-learning configurations, with the goal of balancing performance across tasks and reducing the resources required for model selection.