Optimization for Classical Machine Learning Problems on the GPU

Machine learning problems from optimization perspective

Both optimization and learning play important roles in a system for intelligent tasks. On one hand, we introduce three types of optimization tasks studied in the machine learning literature, corresponding to the three levels of inverse problems in an intelligent system. Also, we discuss three major roles of convexity in machine learning, either directly towards a convex programming or approxima...

Machine learning based decision support for many-objective optimization problems

Multiple Criteria Decision-Making (MCDM) based Multi-objective Evolutionary Algorithms (MOEAs) are increasingly becoming popular for dealing with optimization problems with more than three objectives, commonly termed as many-objective optimization problems (MaOPs). These algorithms elicit preferences from a single or multiple Decision Makers (DMs), a priori or interactively, to guide the search...

Hessian Free Optimization Methods for Machine Learning Problems

In this article, we describe the algorithm and study the performance of a Hessian free optimization technique applied to machine learning problems. We implement the commonly used black box model for optimization and solve a particular challenging recursive neural network learning problem, which exhibits a non-convex and non-di erentiable function output. In order to adapt the method to machine ...

Optimization for Machine Learning

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Optimization for Machine Learning