Tensorization is a model compression technique that breaks down weight tensors of deep neural networks into smaller, lower rank tensors to reveal underlying patterns and reduce...
One of the key drivers behind the rapid expansion in machine learning growth is the technological progress made in the development of...
Machine learning has witnessed a surge in interest in recent years driven by several factors. including the availability of large datasets, advancements in transfer learning...
Machine learning (ML) models are becoming more complex and data-intensive, requiring more expensive hardware and infrastructure to train and run. As a result...
AI has been in an ever expanding renaissance for the past decade, with the success of AlexNet being a pivotal moment which sparked a new wave of deep learning research in 2012. Since then, there have been several step change moments, such as the success of reinforcement learning algorithms on...
