Notes on adversarial network

These days, I heard a lot about un-/semisupervised learning. Ivan Titov’s workshop at the beginning of this month is all about it and now Facebook published a blog post about unsupervised learning for images and videos. They use adversarial networks, i.e. one neural network generates images and another tries to differentiate between authentic and generated images. The first network is trained to fool the other and the second network is trained not to be fooled. Continue reading

Hyperparameter tuning in SURFsara HPC Cloud

Hyperparameter tuning is difficult, not because it’s terribly complicated but obtaining enough resource is often not easy. I’m lucky enough to work at Vrije Universiteit and therefore can access the SURFsara HPC Cloud with not too much effort. Compared to Amazon EC2 (the only other cloud solution I have tried before), the functionality is rather basic but I think suits the needs of many researchers. Using the web interface or OpenNebula API, you can easily customize an image, attach hard drive, launch 10 instances and access any of them using a public key. What else do you need to run your experiments? Continue reading