## Statistics on Manifolds

I think this is a new and hot topic right now since it, at least, helps us on density estimation more efficiently. An expert recommend a book “Statistics on Special Manifolds” by Yasuko Chikuse to me. The book can be found by the link here. The book is so expensive ^_^. However, we can somehow manage to find some papers by the same auther to read. These are the papers listed:

- Density estimation on the spaces of symmetric and rectangular matrices (1997)
- Density estimation on the Stiefel manifold (1998)
- Density estimation on Grassmann Manifolds (2002)

There are quite a number of the application paper related to machine learning, but I haven’t had enough time to review them and say which one is a good paper to read yet.

## Linear Algebra and Applications

I found a lot of interesting topics on linear algebra in the journal called “Linear Algebra and its Applications” by Elsevier Inc. The link below is an example of the journal.

## How to fix “Invalid Numeric Entry” Bug in Photoshop CS3

I encounter this problem a lot, and it’s really annoying. I found a video clip on YouTube.com show how to fix the bug. I tried it, and it works!

Instructions:

- Download Microsoft application called “AppLocale Utility”
- Install the application
- Run AppLocale Utility
- Browse to the Photoshop CS3 program folder “C:\Program Files\Adobe\Adobe Photoshop CS3” and choose the “Photoshop.exe”
- Then select the Greek (Ελληνικά)
- Enjoy using Photoshop CS3 without any problem!

For more detail, please refer to the link http://www.youtube.com/watch?v=lyaKCs4Ls8A

I got the information from the link above too.

## Statistical Physics Algorithms in Machine Learning

Recently I let myself exposed to so many types of problems in machine learning that need pretty high-level techniques to deal with. I was so amazed that most of the methods are originated from Statistical Physics!!! The first one that I encounter is mean field algorithm which is like an invitation for me to other methods in statistical Physics such as Bethe free energy approximation, Kikuchi approximation, saddle point approximation, calculus of variations, etc. I guess there are a lot more and they are very useful for machine learning especially for graphical models framework in which the number of configurations can be intractable.

There are some materials that I found interesting

**Constructing Free Energy Approximations and Generalized Belief Propagation Algorithms**

by Jonathan S. Yedidia, William T. Freeman, and Yair Weiss

**CCCP algorithms to minimize the Bethe and Kikuchi free energies: Convergent alternatives to belief propagation**

by A. L. Yuille

**Statistical Physics Algorithms That Converge**

by A. L. Yuille and J. J. Kosowsky

**Statistical Physics, Mixtures of Distributions, and the EM Algorithm**

by Alan L. Yuille, Paul Stolorz, Joachim Utans

**Statistical Physics of Clustering Algorithms**

by Thore Graepel, Eckehard Sch, Prof Dr, Prof Dr, Klaus Obermayer

## Book: Caring for Your Baby and Young Child

I found this book is very good for taking care of baby and young child. The book covers all the things parents should know about how to raise their young one from birth to age of 5. The content ranges from clothes, diseases, behavior, easy diagnosis, etc. I really recommend new parents to read this book.

http://www.amazon.com/Caring-Your-Baby-Young-Child/dp/0553379623

## Learning Japanese

I came across this blog very helpful for learning Japanese. The blog contains tons of e-books, video courses, learning softwares, Japanese movies, Japanese aminations, etc. You can find all Japanese things there. Also you can download them!