In this study, we provide a direct comparison of the Stochastic Maximum Likelihood algorithm and Contrastive Divergence for training Restricted Boltzmann Machines using the MNIST data set. We ...

Understand how approximation algorithms compute solutions that are guaranteed to be within some constant factor of the optimal solution. Develop a basic understanding of how linear and integer ...

Learn algorithms in an engaging, flexible, and practical way with video tutorials. Find the best video tutorials for different levels, languages, and domains.

This paper presents a short (and not exhaustive) introduction to the most used exact, approximation, and metaheuristic algorithms for solving hard combinatorial optimization problems. After ...

When you need to solve a hard optimization problem, you might resort to using an approximation algorithm, which is a fast and efficient way to find a near-optimal solution. But how do you measure ...

This paper demonstrates a Remez exchange algorithm applicable to approximation of real-valued continuous functions of a real variable by polynomials of degree smaller than n with various linear ...