Saturday, November 28, 2020

The Five Years of the Linux Desktop

 I've been using Linux exclusively - desktop, laptop, and server - for about five years now. It's been a really great experience, and it's been fun to see the world move in the same direction. Microsoft bought github, introduced WSL, and "loves Linux" now, apparently. Well, better than the "Linux is a cancer" MS view of old. We now teach R on a web server rather than SPSS on Windows, and test using OpenSesame on JATOS, rather than E-prime on Windows. I made some new friends at the local LUG and Tech Jam. It's been quite a ride. Looking forward to the next five years.

Monday, September 7, 2020

h = 24


Nine months after reaching 23, my Google Scholar h-index is now 24. The steady progress of this index continues.

Monday, May 11, 2020

Computers: 20 years on

Just added 32GB of memory to my home desktop, bringing the total to 40GB.  This is 300 times more memory than my top-end work desktop in 2000. And it's twice the size of that machine's hard drive.

Wednesday, January 29, 2020

Define 'Highly Cited'

It might be this:
LeCun, Y., Bottou, L., Bengio, Y., & Haffner, P. (1998). Gradient-based learning applied to document recognition. Proceedings of the IEEE, 86(11), 2278-2324.
This paper introduced convolutional (weight-sharing) networks - now popularly known as Deep Neural Networks - and showed they could be used in real-world problems. Cited 24,100 times, according to  Google Scholar (2020-01-29) - over 1,000 citations per year on average.

Oh and - psychologists take note - published in conference proceedings.
Not a one off. How about this conference paper. It's by Simonman & Zisserman, it's a development of the LeCun paper, it was published in 2009, and has averaged 5,500 citations per year.

Tuesday, January 14, 2020

h = 23

My Google scholar h-index just hit 23, about 8 months since the last rise. Steady progress, I guess...

Saturday, November 9, 2019

Donation to GNU Octave

Donated $10 to GNU Octave, a free software replacement for MATLAB. A key resource to liberate scientific code from proprietary software.

Tuesday, July 2, 2019

Science is not advertising...or shouldn't be

“Six stone lighter now. I have more energy and feel healthier than I have for a long time” 
- Shirley Hardy, Atkins diet
Back in November 2018, a few of my colleagues read a recently-published article in Psychonomic Bulletin & Review. The article concerned the evidence for dissociable learning processes in comparative and cognitive psychology. We had all previously critiqued, in print, some part of the evidence presented. We had no particular reason to assume that the authors would agree with our critiques --- and that's fine, it's all part of the continuing debate and dialogue of science. What was perturbing was that the review had largely been written as if no such critiques existed.

In our response, (now accepted by PB&R) we coined the term testimonial review for this type of article. The term refers to a well-known technique in advertising where one promotes a product by highlighting cases that put your product in a good light. Of course, you can't scientifically evidence a claim simply by reporting the data that supports it. One has to consider both the evidence for, and against. You weigh the evidence and come to a conclusion. Good science involves showing your working, so one would expect this process of weighing evidence to be part of any scientific review paper. We call this a balanced review.
Testimonial reviews are not good science. They are potentially misleading, and may result in others basing their own work around the incorrect assumption that a particular issue is resolved. Science isn't advertising ... or, at least, it shouldn't be.