One of the most repeated mantra’s of Machine Learning is that “A Causation is not a Correlation!” When faced with…
Advances in Convex NMF: Linear Programming
Today I am going to look at a very important advance in one of my favorite Machine Learning algorithms, NMF…
cloud-crawler : an open source ruby dsl and distributed processing framework for crawling the web using aws
cloud-crawler-0.1 For the past few weeks, I have taken some time off from pure math to work on an open…
Foundations: Theory of Compressed Sensing
Introduction: In an much earlier post, we looked at detecting Gravity Waves using Machine Learning and techniques like Minimum Path…
Noisy Time Series II: Earth Quakes, Black Holes, and Machine Learning
Recently , 7 Italian Scientists have been sentenced in prison for manslaughter for failing to predict an Earthquake in 2009 !…
Modeling Noisy Time Series: Least Squares Spectral Analysis
Today we consider the problem of modeling periodic behavior in a noisy time series. This is an old problem from…
Data Spectroscopy: Gaussian Kernels and Harmonic Oscillators
Previously we developed some intuition behind the Radial Basis Function / Gaussian Kernel by looking at its Fourier components. We learned that…
Spectral Clustering: A quick overview
A lot of my ideas about Machine Learning come from Quantum Mechanical Perturbation Theory. To provide some context, we need…
Kernels, Green’s Functions, and Resolvent Operators
Machine Learning uses Kernels. At least it tries when it can. A Kernel is an operator on a Hilbert Space.…
Eigenvalue-Independent Effective (Semantic) Operator
This post is still just sketch of ideas…not ready for consumption In my last post I introduced the Eigenvalue-Dependent Effective (Semantic)…
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