Four short links: 8 May 2017

Skimming Text, Image Attribute Transfer, Reproducible Research, and Robots Surviving Clutter

By Nat Torkington
May 8, 2017
  1. Learning to Skim TextDespite their promise, many recurrent models have to read the whole text word by word, making it slow to handle long documents. For example, it is difficult to use a recurrent network to read a book and answer questions about it. In this paper, we present an approach of reading text while skipping irrelevant information if needed. The underlying model is a recurrent network that learns how far to jump after reading a few words of the input text. Basically implementing a teenager reading for school, then. (via hardmaru on Twitter)
  2. Visual Attribute Transfer through Deep Image Analogy — the sample images are stunning.
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  4. Practice of Reproducible Research31 case studies of reproducible research workflows, written by academic researchers in the data-intensive sciences. Each case study describes how the author combined specific tools, ideas, and practices in order to complete a real-world research project. Emphasis is placed on the practical aspects of how the author organized his or her research to make it as reproducible as possible.
  5. Manipulation Under Clutter and Uncertainty With And Around People (YouTube) — an hour-long lecture on the challenges of robotics in actual human environments. I hope they take a while to solve this problem, because hiding in my kid’s room is literally my only survival plan for the robopocalypse.
Post topics: Four Short Links