A paper written by University of Florida Computer & Information Science & Engineering, or CISE, Professor Sumit Kumar Jha, Ph ...

Abstract: Data is growing explosively in digital world, which requires efficient technique to store and transmit data. Because of limited resources, we need data compression (DC) techniques to ...

A new study by Shanghai Jiao Tong University and SII Generative AI Research Lab (GAIR) shows that training large language models (LLMs) for complex, autonomous tasks does not require massive datasets.

byPhotosynthesis Technology: It's not just for plants! @photosynthesis Cultivating life through Photosynthesis, harnessing sunlight to nourish ecosystems and fuel a sustainable future.

Recently, the ConFIG method has also been applied to train physics-constrained generative models: Flow Matching Meets PDEs: A Unified Framework for Physics-Constrained Generation, Giacomo Baldan, ...

Over the past decades, computer scientists have developed many computational tools that can analyze and interpret images. These tools have proved useful for a broad range of applications, including ...

Ready to unlock your full math potential? 🎓Follow for clear, fun, and easy-to-follow lessons that will boost your skills, build your confidence, and help you master math like a genius—one step at a ...

I was wrting my own python version of the host program where I didn't do stochastic verify, and this problem shows up. Somehow this issue was not showing up with the integer case in the original ...

Learn what inventory accounting is, how it works, and key methods like FIFO, LIFO, and WAC. Includes real-world examples, tips, and best practices. I like to think of inventory accounting like ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of computing a matrix inverse using the Newton iteration algorithm. Compared to other algorithms, Newton ...

Dozens of machine learning algorithms require computing the inverse of a matrix. Computing a matrix inverse is conceptually easy, but implementation is one of the most difficult tasks in numerical ...