Gradient ascent is based on the principle of locating the greatest point on a function and then moving in the direction of the gradient. In this method, the gradient function is the function of x and ...

Investigating the mathematics of gradient descent in Linear Regression Machine Learning models: How are linear regression machine learning models effectively constructed using mathematics to generate ...

Machine learning algorithms are programs that can learn from data and previous experience. These algorithms require some parameters which need to be finely tuned for optimal performance. This is ...

Contact person: Riccardo De Bin Keywords: gradient boosting; first-hitting-time models; informative censoring; structural missingness; survival analysis Research group: Statistics and Data Science ...

Proximal gradient descent and its accelerated version are resultful methods for solving the sum of smooth and non-smooth problems. When the smooth function can be represented as a sum of multiple ...