www abstract due today

Today is the abstract due. I have uploaded the abstract.

As I'm leaving on 29th, I need to finish the paper in 3 days!!!

This time, we did some interesting work rather than conventional data mining (mostly focus on cross-validation result, not interesting enough).

Hopefully we can make it!

Travel Plans this year

10/30/ - 11/07, Hongkong, for CIKM.
Presenting "scalable learning of collective behavior based on sparse social dimensions"

12/06 - 12/09, Miami, FL for ICDM.
Presenting "uncovering groups via heterogeneous interaction analysis"

An interesting reading

I came accross this interesing paper by a statistician Leo Breiman talking about the difference of statistics and machine learning. Basically, there are two school: one takes the data model, trying to understand the nature process (which is widely studied by statistician), the other one  takes an algorithmic model. They do not care the process in the black box, but just try to approximate the process using whatever effective methods such as neural network and decisions trees (this is the philosophy of machine learning guys).


Some of the discusssions are very incisive. Leo argued that the over emphasize of data model might lead to wrong conclusions. As there could be many different but comparable models to achieve the same performance. Taking a machine learning approach seems more practical.



I am more interested in reading a paper by a machine learning guy talking about statistics. 


Especially, for a newbie to work on machine learning, should he go to the statistics department or computer science department?

refeshing by writing papers

I'm not sure whether this is a good symptom for reseachers. I feel excited when I write papers. This has been confirmed many times.

starting job search

After submitting all the journal papers relevant to my past work, I'm now ready to look for jobs.

Go Go Go!

Hope I can find an ideal job :)