Learning to Learn Localization
The problem of how to recognize and localize objects on images is well-studied and gained very promising result in computer vision …
Object Recognition using Bag of SIFT-based Features Model
Object Recognition has been one of the most increasingly important issues in Image Processing, finding applications in Computer Vision, …
Topic Model with Nonnegative Matrix Factorization
We define a topic modeling to partition documents into associated topics with nonnegative matrix factorization (NMF). We apply …
Bayesian Analysis of Stochastic Volatility Model And Estimating Volatility with Gibbs Sampler
Stochastic volatility models are those in which the volatility of a stochastic process is itself randomly distributed. There are two …
Finding Underlying Trends and Clustering of Time Series with Non-negative Matrix Factorization and K-Means
In order to reveal similarities and differences in time-series, finding underlying hidden trends, can be thought as all trends which …
Monte Carlo toys: Inversion and Rejection Sampling examples
Monte Carlo methods are the techniques which used in computing estimates via sampling. These methods are highly used within the range …
