Close

Selected Papers in Machine Learning

The Discipline of Machine Learning by Tom Mitchell Introduction to Support Vector Machines - Dustin Boswell Fast Training of Support Vector Machines using Sequential Minimal Optimization Introduction to linear regression The elements of statistical learning (book) Survey of Clustering Algorithms Supervised Machine Learning: A Review of Classification Techniques Ensemble Methods in Machine Learning The Boosting Approach to…

Share

Customizing Conditional Probability using Code Generation with SamIam

Even though every machine learning practitioner and researcher would like to modify and tweak both the algorithm and parameters, there are limited options for automated code generation in the machine learning world. SamIam by Automated Reasoning Group, UCLA is the tool designed for “Sensitivity Analysis, Modeling, Inference and more”. Currently the sensitivity, MAP, MPE and EM Learning…

Share

On Uninformative priors of Bayesian Inference

Since calling this post just On the history of Bayesian inference will be non sequitur. Judea Pearl won the ACM Turing Award, widely considered the "Nobel Prize in Computing" for his contribution in the areas of developing "Novel Framework for Reasoning under Uncertainty that Changed How Scientists Approach Real World Problems". This framework is the notion of Bayesian Networks aka Bayesian Belief Networks…

Share

What are Bayesian Belief Networks? An overview with Eugene Charniak

Bayesian Network without tears by Eugene Charniak of Brown university, is a classical introductory writing by the author of seminal texts like Statistical Language Learning, Introduction to Artificial Intelligence, Artificial Intelligence Programming  and Computational Semantics. It has repeatedly been (officially or unofficially) made part of PhD comprehensive exam reading lists. This short and well-written 14 page paper published…

Share

A framework for mining interesting pattern sets by Bie, Kontonasios and Spyropoulou – A Review

Subjectivity of an interestingness measure has been a subject of discussion for a while in the data mining and machine learning communities. In their SIGKDD paper titled “A framework for mining interesting pattern sets”, authors Bie, Kontonasios and Spyropoulou have suggested a framework, which approaches the problem in a dual-attack manner. Assuming that the prior…

Share