Computer Science News
Computer Science researchers receive the best paper award at the 2018 Internet Measurement Conference (IMC)
The paper "On the Origins of Memes by Means of Fringe Web Communities", by Savvas Zannettou, Tristan Caulfield, Jeremy Blackburn, Emiliano De Cristofaro, Michael Sirivianos, Gianluca Stringhini, and Guillermo Suarez-Tangil, received the best paper award at the 2018 Internet Measurement Conference (IMC), held in Boston this week.
Internet memes are increasingly used to sway and manipulate public opinion. This prompts the need to study their propagation, evolution, and in?uence across the Web. In the paper, the researchers detect and measure the propagation of memes across multiple Web communi... [more]
Cogent Labs and UCL will pursue a unique joint research approach where AI research will be long term and ongoing, fully collaborative with researchers from both institutions working together, with all results being made public and shared with the wider AI community and society at large.
UCL researchers bring extensive AI expertise and established relationships with the international academic community while CL, in addition to its research team, will contribute with its strong machine learning team lead by David Cournapeau, the original author of the globally used machine learning library Sci... [more]
Great Ormond Street Hospital and UCL partnership set to revolutionise how technology is used in hospitals
A new unit set to transform the use of technology including artificial intelligence in healthcare and improve patient outcomes is being opened at Great Ormond Street Hospital (GOSH). The state-of-the-art unit, called DRIVE – Digital, Research, Informatics and Virtual Environments – is the first of its kind in the world. It is both a physical and conceptual unit and is the result of a unique partnership between GOSH, UCL and leading industry experts in technology, artificial intelligence and digital innovation.
The idea behind DRIVE is to create a unique informatics hub to harness the power o... [more]
The paper, Learning on the Edge: Explicit Boundary Handling in CNNs, proposes an innovative solution as an alternative to commonly used padding strategies in convolutions for Convolutional Neural Networks. The main insight is represented by the fact that standard padding strategies introduce a bias that is propagated through the entire pipeline. The alternative presented in the paper allows networks to learn to alleviate this bias on their own. The method proved to be more effective than established strategies on a variety of image processing tasks such as De-bayering and Colorization. For m... [more]