Older blog entries for sness (starting at number 4733)

Christopher M. Bishop

Christopher M. Bishop: "This leading textbook provides a comprehensive introduction to the fields of pattern recognition and machine learning. It is aimed at advanced undergraduates or first-year PhD students, as well as researchers and practitioners. "

'via Blog this'

Syndicated 2012-12-12 15:19:00 from sness


The main
outcome of our analysis is that, for classification, the hinge loss appears
to be the loss of choice. Other things being equal, the hinge loss leads to
a convergence rate practically indistinguishable from the logistic loss rate
and much better than the square loss rate. Furthermore, if the hypothesis
space is sufficiently rich, the bounds obtained for the hinge loss are not
loosened by the thresholding stage.


'via Blog this'

Syndicated 2012-12-12 15:16:00 from sness

CS6240: Parallel Data Processing in MapReduce

CS6240: Parallel Data Processing in MapReduce: "Pig; MapReduce design patterns Read the Pig paper. Read chapters 8 and 11 in the Tom White book."

'via Blog this'

Syndicated 2012-12-11 20:16:00 from sness

How to process a million songs in 20 minutes « Music Machinery

How to process a million songs in 20 minutes « Music Machinery: "The recently released Million Song Dataset (MSD), a  collaborative project between The Echo Nest and Columbia’s LabROSA is a fantastic resource for music researchers. It contains detailed acoustic and contextual data for a million songs. However, getting started with the dataset can be a bit daunting. First of all, the dataset is huge (around 300 gb) which is more than most people want to download.  Second, it is such a big dataset that processing it in a traditional fashion, one track at a time, is going to take a long time.  Even if you can process a track in 100 milliseconds, it is still going to take over a day to process all of the tracks in the dataset.  Luckily there are some techniques such as Map/Reduce that make processing big data scalable over multiple CPUs.  In this post I shall describe how we can use Amazon’s Elastic Map Reduce to easily process the million song dataset."

'via Blog this'

Syndicated 2012-12-11 19:00:00 from sness

HiToRiGoTo: Font problems using Texmaker on Ubuntu 10.04

HiToRiGoTo: Font problems using Texmaker on Ubuntu 10.04: "Font problems using Texmaker on Ubuntu 10.04
I was trying to use Texmaker for an ACM paper, and it was constantly giving me errors like "Font OT1/ptm/m/n/10=ptmr7t at 10.0pt not loadable: Metric (TFM) file not found."
The problem was solved by running $
sudo apt-get install texlive-fonts-recommended


"

sudo aptitude install texlive-fonts-recommended texlive-fonts-extra

Syndicated 2012-12-11 18:46:00 from sness

Ruby Advent Calendar 2012 - Qiita

Ruby Advent Calendar 2012 - Qiita: "yoppi@github が投稿しました
メソッド内で生成されるインスタンスをstubしたいときにdouble rubyとrspec-mocksを使って書く Ruby
"

'via Blog this'

Syndicated 2012-12-11 18:24:00 from sness

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