If Leslie had hit Portugal as hurricane, it would have been the first time in recorded history that Europe had seen the landfall of a hurricane. As it happened, Leslie was officially a hurricane until re-classified as a post-tropical cyclone at 1800 GMT by the National Hurricane Centre in Florida. Leslie made landfall about four hours later, near Coimbra, halfway between the cities of Lisbon and Porto, Portugal. Winds were recorded as 122km per hour in Coimbra but were reportedly as high as 176 km/h at Figueira da Foz. Local media reported many trees down and electricity supplies cut to 15,000 households.
Researchers at CHILI Lab (Ecole Polytechnique Fédérale de Lausanne) in Switzerland and GAIPS Lab (University of Lisbon) in Portugal have recently developed an autonomous system designed to assist children in improving their handwriting skills. The system they created, presented in a paper published in Springer's International Journal of Social Robotics, entails the use of a social robot in one-to-one learning sessions with children. For some children, handwriting can be a difficult skill to acquire, yet it is a fundamental stepping stone in their academic path. In fact, poor handwriting can negatively affect a child's academic performance, self-esteem and learning motivation. To master handwriting, a child needs to learn to coordinate cognitive, motor and perceptual abilities, thus he/she might also require a considerable amount of practice.
A Classification-Based Approach to Semi-Supervised Clustering with Pairwise Constraints Marek Smieja a,, Łukasz Struski a, Mário A. T. Figueiredo b a Faculty of Mathematics and Computer Science, Jagiellonian University, Kraków, Poland b Instituto de T elecomunicações, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, PortugalAbstract In this paper, we introduce a neural network framework for semi-supervised clustering (SSC) with pairwise (must-link or cannot-link) constraints. In contrast to existing approaches, we decompose SSC into two simpler classification tasks/stages: the first stage uses a pair of Siamese neural networks to label the unlabeled pairs of points as must-link or cannot-link; the second stage uses the fully pairwise-labeled dataset produced by the first stage in a supervised neural-network-based clustering method. The proposed approach, S 3 C 2 (Semi-Supervised Siamese C lassifiers for C lustering), is motivated by the observation that binary classification (such as assigning pairwise relations) is usually easier than multi-class clustering with partial supervision. On the other hand, being classification-based, our method solves only well-defined classification problems, rather than less well specified clustering tasks. Extensive experiments on various datasets demonstrate the high performance of the proposed method. Keywords: semi-supervised clustering, deep learning, neural networks, pairwise constraints 1. Introduction Clustering is an important unsupervised learning tool often used to analyze the structure of complex high-dimensional data. Semi-supervised clustering (SSC) methods tackle this issue by leveraging partial prior information about class labels, with the goal of obtaining partitions that are better aligned with true classes [1, 2, 3, 4, 5, 6]. One typical way of injecting class label information into clustering is in the form of pairwise constraints (typically, must-link and cannot-link constraints), or pairwise preferences (e.g., should-link and shouldn't-link), which indicate whether a given pair of points is believed to belong to the same or different classes. Most SSC approaches rely on adapting existing unsupervised clustering methods to handle partial (namely, pairwise) information [7, 8, 4, 5, 6, 9].
This week, we bring you the first VB Engage to have been recorded live on stage! That's right: At Web Summit in Lisbon earlier this year, we got to interview Alan Schaaf of internet phenomenon Imgur about the evolution of the company, geek culture, community, and what it takes to create a success from seemingly meagre beginnings. In the news segment, Travis quizzes Stewart about his trip to Helsinki (where he spoke at Nexterday North and Slush), and discovers what he learned about the near future, artificial intelligence, mobile marketing, and where technology is taking us next.
German luxury car maker Daimler is set to combine a range of digital customer support experiments into a single voice-activated app that is available whether users are driving their cars, sitting at home or on the go. Chief digital officer Sabine Scheunert said on Tuesday that Daimler will soon introduce a digital assistant called'Ask Mercedes' that ties together previous trial projects on platforms such as Google and Facebook. Scheunert said'Ask Mercedes' will be available in several markets and languages immediately before being rolled out globally, without providing further details. 'Ask Mercedes is a new cognitive assistant available any time to support customers in exploring all the functions of their Mercedes-Benz vehicles,'the firm said at the Lisbon Web Summit. Mercedes is one of Daimler's leading car brands.