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Vector Magic

Author:nick @ January 30th, 2008 Leave a Comment

This site was recommended by a Cognitive Science student. It is a utility for converting images to vector graphics. It is useful for turning things like images of logos, figures, etc. that don’t scale well into vector graphics that do.

I haven’t yet tried it out, but you may want to at some point.

Matlab ‘sample’ function

Author:nick @ January 30th, 2008 Leave a Comment

I recently discovered Matlab’s “sample” function, which I have implemented on my own several times before. There are always slightly annoying implementation details to work out, and it’s very nice to have a function that is standard to do it for me.

The idea is to sample from a multinomial distribution, which is something you need to do from time to time for various reasons. Here is an example of usage:

>> sample([.25, .5, .1, .15],1),  ans =  3
>> sample([.25, .5, .1, .15],1),  ans =  4
>> sample([.25, .5, .1, .15],1),  ans =  1
>> sample([.25, .5, .1, .15],1),  ans =  4
>> sample([.25, .5, .1, .15],1),  ans =  2
>> sample([.25, .5, .1, .15],1),  ans =  1
>> sample([.25, .5, .1, .15],1),  ans =  2
>> sample([.25, .5, .1, .15],1),  ans =  2

a = sample([.25, .5, .1, .15],10000);
>> nnz(a == 1),  ans =  2483
>> nnz(a == 2),  ans =  5027
>> nnz(a == 3),  ans =  988
>> nnz(a == 4),  ans =  1502

Approach to improve face recognition

Author:micahrye @ January 28th, 2008 Leave a Comment

from article “Accurate face recognition is critical for many security applications. Current automaticface-recognition systems are defeated by natural changes in lighting and pose, which often affect face images more profoundly than changes in identity. The only system that can reliably cope with such variability is a human observer who is familiar with the faces concerned. We modeled human familiarity by using image averaging to derive stable face representations from naturally varying photographs. This simple procedure increased the accuracy of an industry standardface-recognition algorithm from 54% to 100%, bringing the robust performance of a familiar human to an automated system.” Face Recognition Article

ICDL 2008: Deadline for Papers is March 14

Author:movellan @ January 21st, 2008 Leave a Comment

This year is in Monterrey, California
August 9th-12th, 2008.

Important dates:
Feb. 15 Special session proposals due
March 14 Full 6-page paper submissions due
March 21 Tutorial proposals due
April 14 Notification of accept/reject
April 18 1-page poster abstracts due
May 9 Camera-Ready Copy due

Open Source Speech Recognition

Author:micahrye @ January 19th, 2008 Leave a Comment

From Slashodot  Open Source Speech Recognition artical

AAAI deadline soon

Author:ianfasel @ January 18th, 2008 Leave a Comment

AAAI may also be a decent venue for some of the projects done in mplab.  Here is a link to past conferences to get an idea: deadline for the 2008 conference is Jan 30, though some have abstracts due on the 25th.  Here’s the link: 

ICML and UAI deadlines soon

Author:ianfasel @ January 18th, 2008 Leave a Comment

ICML and UAI have about the same audiences as NIPS.  I’m not sure what should make you choose ICML versus UAI.  They are opposite in schedule as NIPS: submit in winter, conference in summer.  So a lot of people basically make two conference trips per year.  This year UAI, ICML, and COLT are at the same place and location.Feb 8: ICML deadlineFeb 27: UAI abstract deadline, Feb 29 full submission. 

Letter of Concern About Preuss Audit

Author:movellan @ January 16th, 2008 Leave a Comment

A group of university professors has written a letter of concern about the recent audit of the Preuss School.


The Association of California School Administrators Recently Sent Another Letter of Concern

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