A laboratory study using machine learning to optimize hydrothermal production of carbon quantum dots from tea processing ...
Ed Ahearne combined automation , machine learning and Bayesian optimization to speed up method development for siRNA medicines. At ISC 2016, Edward Ahearne of AstraZeneca’s Pharmaceutical Sciences - ...
A simulation study reported machine-learning predictions of bearing-capacity and safety factors for ring foundations in ...
Fully updated to reflect modern developments in the field, the Fifth Edition of An Introduction to Optimization fills the need for an accessible, yet rigorous, introduction to optimization theory and ...
Chemists routinely optimize reactions to maximize the yield of their desired products, but understanding why those reactions work can require laborious experiments that track reactions through time.
Machine learning models, also called artificial intelligence models, have made astonishing leaps in complexity in recent years and are entering the public realm en masse. Highly visible examples are ...
Stochastic gradient descent and Adam are optimization algorithms that update model parameters from estimated gradients, but they use different rules for momentum and per-parameter step sizes. This ...
Machine learning and AI are transforming how businesses operate: improving efficiency, streamlining workflows, establishing consistency, maintaining security and compliance, and creating new ...
Machine Learning is an important area of research and practice influencing many diverse application domains and industries. Students may add this concentration to any degree within the College of ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results