Microchip Technologies' Brette Mullenaux delves into post-quantum cryptography and how it is reshaping the approach to ...

Probabilistic models, such as hidden Markov models or Bayesian networks, are commonly used to model biological data. Much of their popularity can be attributed to the existence of efficient and robust ...

Abstract: Many distributed optimization algorithms critically depend on careful step-size tuning to ensure stability and achieve fast convergence. In this work, we address this limitation in the ...

Machine learning is the ability of a machine to improve its performance based on previous results. Machine learning methods enable computers to learn without being explicitly programmed and have ...