Clustering using tagging or indexation methods (see section 3 after clicking on the link), allowing you to cluster text (articles, websites) much faster than any traditional statistical technique, with a scalable algorithm very easy to implement Bucketization - the science and art of identifying the right homogeneous data buckets (millions of buckets among billions of observations), to provide highly localized (or segment-targeted) predictions, or to smooth regression parameters across similar buckets, with strong statistical significance. It is equivalent to joint (not sequential) binning in multiple dimensions, which is a combinatorial optimization problem. While decision trees also produce some bucketization, the data science approach is more robust, simple, scalable and model-free. It does not directly produce decision trees, and lead to easy interpretation (each data bucket corresponding to a specific type of fraud, in a fraud detection problem). A related problem is bucket clustering, via standard hierarchical clustering techniques.

We propose a new proximal, path-following framework for a class of constrained convex problems. We consider settings where the nonlinear---and possibly non-smooth---objective part is endowed with a proximity operator, and the constraint set is equipped with a self-concordant barrier. Our approach relies on the following two main ideas. First, we re-parameterize the optimality condition as an auxiliary problem, such that a good initial point is available; by doing so, a family of alternative paths towards the optimum is generated. Second, we combine the proximal operator with path-following ideas to design a single-phase, proximal, path-following algorithm. Our method has several advantages. First, it allows handling non-smooth objectives via proximal operators; this avoids lifting the problem dimension in order to accommodate non-smooth components in optimization. Second, it consists of only a \emph{single phase}: While the overall convergence rate of classical path-following schemes for self-concordant objectives does not suffer from the initialization phase, proximal path-following schemes undergo slow convergence, in order to obtain a good starting point \cite{TranDinh2013e}. In this work, we show how to overcome this limitation in the proximal setting and prove that our scheme has the same $\mathcal{O}(\sqrt{\nu}\log(1/\varepsilon))$ worst-case iteration-complexity with standard approaches \cite{Nesterov2004,Nesterov1994} without requiring an initial phase, where $\nu$ is the barrier parameter and $\varepsilon$ is a desired accuracy. Finally, our framework allows errors in the calculation of proximal-Newton directions, without sacrificing the worst-case iteration complexity. We demonstrate the merits of our algorithm via three numerical examples, where proximal operators play a key role.

Big Tech's AI Predictions for 2017 Lolita Taub The Huffington Post "For the final Cognitive Business post of the year, I asked artificial intelligence centric Fortune 500 leaders for their 2017 enterprise AI predictions. Microsoft, IBM, Baidu, NVIDIA, Qualcomm, GE, SAS, and Oracle responded. What they had to say is exciting..." Artificial Intelligence Is Going to Make It Easier Than Ever to Fake Images and Video James Vincent The Verge "Smile Vector is just the tip of the iceberg. It's hard to give a comprehensive overview of all the work being done on multimedia manipulation in AI right now, but here are a few examples: creating 3D face models from a single 2D image; changing the facial expressions of a target on video in real time using a human "puppet"; changing the light source and shadows in any picture... live-streaming the presidential debates but making Trump bald..." Artificial Feathers Let Drones Morph Their Wings Like Birds Evan Ackerman IEEE Spectrum "Thanks to overlapping feathers and a joint at the end of the wing, most birds can fold their primary flight feathers back, which significantly reduces the surface area of their wings... These folding wings can vary their surface area by 41 percent. When the wing is completely retracted, lift decreases by 32 percent, and drag decreases by 40 percent, boosting the top speed of the drone from 6.3 meters per second to 7.6 meters per second."

Enlarge / Semi-automated trucks are driven on the E19 highway in Vilvoorde, Belgium, on April 5, 2016 as part of the'EU Truck Platooning Challenge 2016.' This week, scientists and economic advisers to President Obama released a report on artificial intelligence, including the effects of automation on the US job market and economy. While the report notes the significant potential for wealth gains from increased productivity due to AI, it also warns of threats to existing jobs and an exacerbation of the wage inequality between lower-skilled, less-educated workers and those with higher skills. In recent decades, automation has already claimed occupations such as those of switchboard operators, filing clerks, travel agents, and assembly line workers, and it is now on the cusp of replacing driving-related occupations such as taxi and Uber drivers. Automation will probably move into the trucking industry within a decade (3.8 million US jobs are related to driving).

The ASA contacted the Statistical Consulting and Survey Center in the Augusta University Department of Biostatistics to help design and analyze the data for a survey of the association's nonacademic members in the United States employed by business, industry, or government. Members were asked to report their annual base salary (in dollars) and instructed to include bonuses, incentives, or other forms of monetary reward. Salary was "annualized" for part-time employed respondents. All salary statistics are reported as full-time equivalents in dollars per year. Salary information, in the form of percentiles, is for a 12-month period.

Mark Zuckerberg has spend time and effort the whole year developing his personal AI butler as his New Year's resolution, Time reported. This means, he is creating an AI that somehow is like Tony Stark's "Jarvis." His major takeaway from the project is that no matter how much advancement the AI industry has reached, it still requires an ample amount of guidance from humans. Another top AI story is the AI 2020 competition that XPRIZE launched with IBM Watson, Tech Crunch reported. XPRIZE is the non-profit organizsation that contributed to the success of SpaceShipOne in 2004.

Google's use of machine learning and artificial intelligence to better understand search intention and deliver the most relevant results is resulting in just that, according to new research from SEO and content performance platform Searchmetrics in its annual study of Google ranking factors. According to Searchmetrics, not only are search results more relevant than ever, many simplistic techniques to artificially inflate page rank ‒ like collecting backlinks and increasing the number of times keywords are mentioned in text – are becoming less effective. Backlinks are also becoming less important because of the rise of mobile search queries because pages viewed on mobile devices are often liked or shared but seldom linked to, Searchmetrics added. Searchmetrics analyzed the top 20 search results for 10,000 keywords on Google.com. The goal was to identify the key factors that high-ranking pages have in common.

REVOLVING DOOR -- "Trump appoints his business attorney to manage international negotiations," by CNN's Elise Labott and Teddy Schleifer: "Jason Greenblatt, the executive vice president and chief legal officer for Trump's business empire, will take on the title of special representative for international negotiations. A source familiar with the appointment told CNN that Greenblatt will primarily will be working on Israel-Palestinian peace process, the American relationship with Cuba and trade agreements."

French woman Lilly wants to marry her robot. Only her partner is 3D printed robot named Inmmovator who she designed herself, after realising she was attracted to "humanoid robots generally" rather than other people. "I'm really and totally happy," she told news.com.au "Our relationship will get better and better as technology evolves." The "proud robosexual" said she always loved the voices of robots as a child but realised at 19 she was sexually attracted to them as well.

A Nobel Prize-winning economist has warned that the rise in robotics and automation could destroy millions of jobs across the world. Angus Deaton, who won the Nobel Prize last year for his work on health, wealth, and inequality, told the Financial Times he believes robots are a much greater threat to employment in the US than globalisation. Addressing the theory that Donald Trump's victory in the US presidential elections was fueled by a backlash against globalisation, Deaton told the FT: "Globalisation for me seems to be not first-order harm and I find it very hard not to think about the billion people who have been dragged out of poverty as a result. I don't think that globalisation is anywhere near the threat that robots are." He added: "It's hard to think that Mark Zuckerberg is actually impoverishing anyone by getting rich with Facebook. But driverless cars are another matter entirely."