Archive for the ‘Posted by Greg Ver Steeg’ Category

Here are the slides from my talk yesterday at ICML. The information sieve is introduced in this paper. But in this followup paper, we make it really practical and demonstrate the connections to “common information”. The code is on github for the discrete and continuous versions.

This one is just for fun. There’s no deeper meaning, just a failed experiment that resulted in some cool looking pictures.

  You have just eaten the most delicious soup of your life. You beg the cook for a recipe, but soup makers are notoriously secretive and soup recipes are traditionally only passed on to the eldest heir. Surreptitiously and with extreme caution, you pour some soup into a hidden soup compartment in your pocket. When […]

Shannon’s birthday has passed, but I thought I would jump on the bandwagon late, as usual. Shannon himself recognized that information theory was so compelling that it encouraged over-use. He wrote an article saying as much way back in the 50’s. It will be all too easy for our somewhat artificial prosperity to collapse overnight […]

As a child, I was visited by an alien. I remember the sensation of not being able to move or speak and seeing this other-worldly face. Some time later, when I saw a documentary about people who had been visited by aliens, I felt a chill of recognition. Their experiences matched my own. People all […]

Once upon a time, a boy from a farm in Iowa got an exciting opportunity to move to the west coast. While many new experiences awaited him there, he found himself imprisoned in a cage made of cars. After many years, he had never managed to escape the prison of cars to do simple things […]

In academic work, page restrictions in publications often mean that there is not enough space to explore interesting but tangential relationships between ideas or to give more than bare-bones proofs of mathematical ideas. I am hoping to remedy this, at least initially, with a webcast series of three talks at ISI. I’ll post the links […]

I just put up a new paper with the (hopefully) intriguing title “The Information Sieve“. The motivation is that when we humans look at the world, we tend to identify a new pattern or learn a new trick, and then we move on to the next thing. There are two amazing things about this: 1. We […]

I admit that this is a bit of a melodramatic title. I was actually a little surprised that, before I used it, the phrase “deep learning for insights” did not exist in google. I gave a talk at eHarmony with this title, for the LA machine learning group. The video is posted here. The original announcement also has […]

I’ve been working on a series of posts about an exciting line of work I’m pursuing. The groundwork is in this paper. The basic idea is that any thing we learn from inputs should be considered a representation. What would happen if we searched over the space of all representations for one that is most informative about […]