Machine Learning Techniques

Publications

Genetic Programming – Computers using “Natural Selection” to generate programs The Future of Genetic Programming – slides

Publications

An As-Short-As-Possible Introduction to the Least Squares, Weighted Least Squares and Moving Least Squares Methods for Scattered Data Approximation and Interpolation THE APPROXIMATION POWER OF MOVING LEAST-SQUARES Moving Least Squares Approximation Moving Least-squares Approximations for Linearly-solvable MDP Surfaces generated by Moving Least Squares Methods Least Squares Methods – What is SPH ? MOVING LEAST SQUARES … Read more

Papers

Towards intelligent machines : Theories, technologies and experiments Optimization strategies for complex engineering applications MACHINE–LEARNING IN OPTIMIZATION OF EXPENSIVE BLACK–BOX FUNCTIONS Deep learning via Hessian-free optimization Improving the Convergence of the Backpropagation Algorithm Using Learning Rate Adaptation Methods Bayesian Optimization for Learning Gaits under Uncertainty An experimental comparison on a dynamic bipedal walker Autoencoders, Unsupervised … Read more

Websites

Alex Minnaar : Deep Learning Basics: Neural Networks, Backpropagation and Stochastic Gradient Descent Neural Networks – A Systematic Introduction – Raul Rojas Neural Networks and Deep Learning –  Michael Nielsen UFLDL Tutorial

Gaussian Process & Genetic Algorithm

Optimization of Gaussian Process Models with Evolutionary Algorithms A genetic Gaussian process regression model based on memetic algorithm Accelerating Evolutionary Algorithms with Gaussian Process Fitness Function Models The Use of Genetic Algorithms for Searching Parameter Space in Gaussian Process Modeling GPfit: An R package for Gaussian Process Model Fitting using a New Optimization Algorithm A COMPARISON BETWEEN GAUSSIAN PROCESS EMULATION … Read more