Four short links: 1 December 2017
Creepy Kid Videos, Cache Smearing, Single-Image Learning, and Connected Gift Guide
- /r/ElsaGate — Reddit community devoted to understanding and tackling YouTube’s creepy kid videos, from business models to software used to create them.
- Cache Smearing (Etsy) — to solve the problem where one key is so powerful it overloads a single server, a technique for turning a single key into multiple so they can be spread over several servers.
- Deep Image Prior — Deep convolutional networks have become a popular tool for image generation and restoration. Generally, their excellent performance is imputed to their ability to learn realistic image priors from a large number of example images. In this paper, we show that, on the contrary, the structure of a generator network is sufficient to capture a great deal of low-level image statistics prior to any learning. In order to do so, we show that a randomly initialized neural network can be used as a handcrafted prior with excellent results in standard inverse problems such as denoising, superresolution, and inpainting. Furthermore, the same prior can be used to invert deep neural representations to diagnose them, and to restore images based on flash/no flash input pairs.
- Privacy Not Included (Mozilla) — shopping guide for connected gifts, to help you know whether they respect your privacy or not. (most: not so much)
