Linear regression, the fitting of linear relationships among variables in a data set, is a standard tool in data analysis. In particular, for the sake of interpretability and utility in further analysis, we desire to find highly sparse linear relationships, i.e., involving only a few variables. Of course, such simple linear relationships often will not hold across an entire population. But, more frequently there will exist conditions - perhaps a range of parameters or a segment of a larger population - under which such sparse models fit the data quite well. For example, Rosenfeld et al. [16] used data mining heuristics to identify small segments of a population in which a few additional risk factors were highly predictive of certain kinds of cancer, whereas these same risk factors were not significant in the overall population. Simple rules for special cases may also hint at the more complex general rules. More generally, we need to develop new techniques to reason about populations in which most members are atypical in some way, which are colloquially (and somewhat abusively) referred to as long-tailed distributions. We are seeking principled alternatives to ad-hoc approaches such as trying a variety of methods for clustering the data and hoping that the identified clusters can be modeled well.

Based on the disturbing number of successful data breaches over the past few years, it's pretty evident that organizations are being overwhelmed by the growing number of threats.

This is part of a series on Artificial Intelligence. If you are catching it for the first time I'd recommend that you start here where I introduce the idea and provide some instrumental background. In the last article, I talked about the usefulness of thinking about artificial intelligence in its chapters. True, you could start biting this elephant anywhere and anyhow. The phases approach is just my recommended way of understanding, with better clarity, the goals and ultimate intentions of AI.

GWEN IFILL: Now: developing technology that can better identify your own emotions. At a time when people are concerned about what data can track and how it can be sold, it is an advance that clearly raises concerns. But it may also yield some important benefits. The "NewsHour"'s April Brown takes a look, part of our weekly series on the Leading Edge of science and technology. DAN MCDUFF, Director of Research, Affectiva: You can control the movements of BB-8, the little droid, based on how your facial expressions are changing.

ISLAMABAD – The U.S. drone strike that killed the Islamic State group's commander for Afghanistan and Pakistan was the latest blow to the Middle East-led movement's ambitions to expand into a region where the long-established Taliban remain the dominant Islamist force. The Islamic State group has enticed hundreds, perhaps thousands, of jihadi fighters in Afghanistan and Pakistan to switch loyalty and has held a small swath of territory in the eastern Afghan province of Nangarhar, where leader Hafiz Saeed Khan was killed on July 26 by a U.S. drone, Washington confirmed late Friday. But outside that pocket of territory, security officials and analysts say that the group remains -- for now -- more of a "brand name" than a cohesive militant force in much of the region. "Groups around the world want to jump on that bandwagon and cash in on their popularity and the fear they command," said a Pakistani police official based in Islamabad, on condition of anonymity because he was not authorized to speak to media. Anxiety over the Islamic State group -- also known as ISIS or "Daesh" -- in Afghanistan and Pakistan has been building since the al-Qaida breakaway movement seized portions of territory in Iraq and Syria in 2014 and began promoting itself worldwide.

Do machine-learning algorithms processing search engine queries bring on prejudice, discrimination and stereotyping in query results? Search results have been known to highlight these negative attributes in the past. Now researchers at Brazil's Universidade Federal de Minas Gerais suggest it could be true when it comes to female physical attractiveness in images available across the Web. The paper submitted to the International Conference on Social Informatics scheduled for publication analyzes how Google and Bing represent female beauty in their image search results, particularly when it comes to different age and racial groups. They then passed the more than 2,000 images through a program, which estimates subject age, race and gender with an estimated 90% accuracy.

Seymour Papert with LEGO Mindstorms robotics kits, which were named in recognition of Papert's seminal book, Mindstorms: Children, Computers, and Powerful Ideas. Seymour Papert with LEGO Mindstorms robotics kits, which were named in recognition of Papert's seminal book, Mindstorms: Children, Computers, and Powerful Ideas. The field of educational technology is mourning a visionary whose work was considered 50 years ahead of its time. Seymour Papert, who died July 31 at age 88, was a mathematician and computer scientist who spent decades at MIT. "Seymour was one of the very first people to recognize that new computer technologies could be used by kids to create things in new ways and express themselves," Mitchel Resnick, a professor of learning research at MIT and a longtime colleague and friend, told NPR Ed. "It's amazing that Seymour was thinking these ideas in the 1960s," Resnick adds, "when computers cost hundreds of thousands of dollars, but he foresaw the day that every child would have access to a computer." The great theme of Papert's work and life was the nature of intelligence, or what he called thinking about thinking.

Asking about the benefits of artificial intelligence and machine learning reminds me a little of the transition to suitcases with wheels. Do you remember lugging around those old suitcases? If not, good for you - this original advertisement from US Luggage will take you back! Thank Bernard Sadow for persistence with his idea to add wheels, because when he pitched his idea people thought he was crazy. Surely no one would want to pull their own suitcase?

Video Friday is your weekly selection of awesome robotics videos, collected by your soft-bodied Automaton bloggers. We'll also be posting a weekly calendar of upcoming robotics events for the next two months; here's what we have so far (send us your events!): Let us know if you have suggestions for next week, and enjoy today's videos. He is currently a visiting researcher in the Morphology, Evolution & Cognition Lab (Vermont Complex Systems Center, University of Vermont, USA) under the supervision of Prof. Josh Bongard. He wrote in to share some of his latest publications and videos, and it's fascinating.

Video Friday is your weekly selection of awesome robotics videos, collected by your baby-loving Automaton bloggers. We'll also be posting a weekly calendar of upcoming robotics events for the next two months; here's what we have so far (send us your events!): Let us know if you have suggestions for next week, and enjoy today's videos. We got a teaser about the Omnicopter during Raff D'Andrea's most recent TED Talk, but this dedicated video shows it off much better: Like all the coolest robots, the things it can do look like CGI, right? On July 27, 2016, Michigan-based Vayu, Inc., in collaboration with the Stony Brook University Global Health Institute completed the first ever series of long-range, fully autonomous drone delivery flights with blood and stool samples, setting records in the process.