Siavash Ebrahimi

Title: Siavash Ebrahimi: Innovator in Resource-Efficient Neural Architectures

Introduction

Siavash Ebrahimi is a prominent inventor based in San Jose, California. He has made significant contributions to the field of neural architecture search, focusing on resource efficiency. His innovative approach addresses the challenges of computational resource use in automated neural architecture search.

Latest Patents

Siavash Ebrahimi holds a patent for a Resource-Efficient Neural Architect (RENA). This invention presents an efficient resource-constrained neural architecture search using reinforcement learning with network embedding. RENA utilizes a policy network to process network embeddings and generate new configurations. The tested embodiment on the CIFAR10 dataset achieved a 2.95% test error with compute intensity greater than 100 FLOPs/byte and a 3.87% test error with a model size of less than 3M parameters. Additionally, for the Google Speech Commands Dataset, RENA achieved state-of-the-art accuracy without resource constraints, outperforming optimized architectures under tight resource constraints.

Career Highlights

Siavash Ebrahimi is currently employed at Baidu USA LLC, where he continues to develop innovative solutions in the field of artificial intelligence. His work emphasizes the importance of balancing performance with resource efficiency in neural networks.

Collaborations

Some of Siavash Ebrahimi's notable coworkers include Yanqi Zhou and Sercan Omer Arik. Their collaborative efforts contribute to advancing research in neural architecture and machine learning.

Conclusion

Siavash Ebrahimi's work in resource-efficient neural architectures represents a significant advancement in the field of artificial intelligence. His innovative approaches are paving the way for more efficient and effective neural network designs.