Scaling and Scalability - Accelerating Ill-conditioned Low-rank Estimation via Scaled Gradient Descent

Scaling and Scalability - Accelerating Ill-conditioned Low-rank Estimation via Scaled Gradient Descent

Explore a keynote presentation from the PROGRESS workshop at ICASSP 2023, delivered by Yuejie Chi from Carnegie Mellon University. Delve into the topic of "Scaling and Scalability: Accelerating Ill-conditioned Low-rank Estimation via Scaled Gradient Descent" in this 48-minute talk. Gain insights into advanced signal processing techniques and their applications in addressing challenges related to ill-conditioned low-rank estimation. Learn about the innovative approach of scaled gradient descent and its potential to accelerate computational processes in this field. Discover how these concepts contribute to the broader landscape of acoustics, speech, and signal processing as discussed at the IEEE International Conference.