I second the call for workshops at ICML/COLT/UAI.
Several times before, details of why and how to run a workshop have been mentioned.
There is a simple reason to prefer workshops here: attendance. The Helsinki colocation has placed workshops directly between ICML and COLT/UAI, which is optimal for getting attendees from any conference. In addition, last year ICML had relatively few workshops and NIPS workshops were overloaded. In addition to those that happened a similar number were rejected. The overload has strange consequences—for example, the best attended workshop wasn’t an official NIPS workshop. Aside from intrinsic interest, the Deep Learning workshop benefited greatly from being off schedule.
Hi!
I realize this is not the right place for asking general questions. Please forgive me , but i am out of ends… Im a grad student and Im learning machine learning for the first time. I have a small problem and I was wondering if you could help me out. I’m programming an algorithm to answer the question “what is fashionable in second life (the game) “. For this I have collected several data sets by observing what people are wearing in this environment.
I have a problem regarding choice of algorithm. Ive studied Tom Mitchells book and in relation to that, my data sets are all “yes†answers. I have no examples of negative instances (ie. “what is not fashionable”) So when I try contructing a decision tree I end up with positive all the time. I guess this is my problem, could you suggest an approach or tell me where Im going wrong? Im sorry to waste ur time 🙂 but Im really unable to find any answers … 🙁
thanks