Conventional collaborative filtering techniques treat a top-n recommendations problem as a task of generating a list of the most relevant items. This formulation, however, disregards an opposite - avoiding recommendations with completely irrelevant items. Due to that bias, standard algorithms, as well as commonly used evaluation metrics, become insensitive to negative feedback. In order to resolve this problem we propose to treat user feedback as a categorical variable and model it with users and items in a ternary way. We employ a third-order tensor factorization technique and implement a higher order folding-in method to support online recommendations. The method is equally sensitive to entire spectrum of user ratings and is able to accurately predict relevant items even from a negative only feedback. Our method may partially eliminate the need for complicated rating elicitation process as it provides means for personalized recommendations from the very beginning of an interaction with a recommender system. We also propose a modification of standard metrics which helps to reveal unwanted biases and account for sensitivity to a negative feedback. Our model achieves state-of-the-art quality in standard recommendation tasks while significantly outperforming other methods in the cold-start "no-positive-feedback" scenarios.

Eye in the Sky Superbly acted, this nail-biter starring Helen Mirren, the late Alan Rickman and Aaron Paul is a fully involving war drama about the new rules of engagement. Hunt for the Wilderpeople This wonderful New Zealand film has a gently absurdist quality, a simultaneously sweet and subversive sensibility all its own, mixing warmth, adventure and comedy in ways that consistently surprise. The Innocents Anne Fontaine's post-World War II drama involving a Polish convent and a French female doctor proves yet again that though moral and spiritual questions may not sound spellbinding, they often provide the most absorbing movie experiences. The Jungle Book By turns sweetly amusing and scarily unnerving, crammed with story, song and computer-generated visual splendors, this revisiting of the old Rudyard Kipling tales aims to be a model of modern crowd-pleasing entertainment. Life, Animated A remarkable documentary about how Disney animated features changed the life of a young autistic boy in a deep and profound way.

PewDiePie bashed reporters Wednesday for singling him out in articles about the Federal Trade Commission and Warner Bros. "pay for play" settlement." In a video uploaded Wednesday -- titled "THE PEWDIEPIE'SCANDAL'!!" -- the Swedish YouTuber (whose real name is Felix Kjellberg) expressed outrage that the FTC would list him as one of the YouTube creators "reviewing" the publisher's game Middle-earth: Shadow of Mordor. The FTC argues the Burbank-based entertainment company failed to adequately disclose that it paid influencers "hundreds to tens of thousands of dollars" to create sponsored videos that only promote the game in a positive way. No particular influencer was named in the FTC settlement itself. However, in its press release, the FTC did mention the "wildly popular" PewDiePie. "It's kind of bullshit," PewDiePie said of the media coverage. "Yes, I could have disclosed it better.

The revolution is here--and it will be televised, Friend. Tonight, in fact, as the highly anticipated season 2 of Mr. Robot premieres. The unusual show struck a chord with audiences last summer and garnered immediate praise from critics and the public, even stealing a Golden Globe from Game of Thrones. Now, the program will have to sustain that interest as it continues the arresting story of Elliot Alderson, a mentally unstable hacker and member of the anarchic hacktivist group fsociety. An amalgam of Fight Club, V is for Vendetta and The Matrix, the show was initially conceived of as a feature film by creator Sam Esmail--but his big-canvas aspirations haven't been lost in the move to smaller screens.

Allison Parrish is a computer programer, educator, and poet whose work deals with the materiality of language. With a background in both the formal study of language (she received her BA in Linguistics from UC Berkeley) and years of experience as a software developer, Parrish's work has lead her to explore words not only as symbols but also as objects in their own right, teasing the boundaries between medium and message to ask questions about how communication happens in a digital context. Electronic media open up entirely new possibilities for the manipulation of language, but they also lay bare some of the thorniest problems of textual interpretation. If we are writing for other humans we can assume a baseline understanding of how language works, an understanding which computers still do not share. If this seems abstract, consider the way that language comes to be represented as a text file in a computer: words are compressed into ASCII characters and stored as bits on a hard drive; the fundaments of human communication, having emerged out of obscure prehistory and evolved for centuries, accumulating layers of connotation and nuance along the way, are now encoded as tiny electrical charges in a matrix of transistors.

By Alissa Quart, author of "The Republic of Outsiders" and "Branded", is the editor for the nonprofit Economic Hardship Reporting Project. Precariousness is not just a working-class thing. In recent interviews, dozens of academics and schoolteachers, administrators, librarians, journalists and even coders have told me they too are falling prey to an unstable new America. I've started to think of this just-scraping-by group as the Middle Precariat. The word Precariat was popularized five or so years ago to describe a rapidly expanding working class with unstable, low-paid jobs.

Everywhere you look today, there are examples cropping up of how machine learning is revolutionising different industries. In media and entertainment, Spotify and Netflix sort through billions of data points to find patterns in music, films and television that consumers have enjoyed -- and then make suggestions based on their tastes. In retail, Amazon prompts consumers to buy everything from nappies to office chairs based on shoppers' previous purchases. In finance, machine learning is helping investors anticipate market trends and powering innovations underlying everything from self-driving cars to voice-assistant applications. In the payments industry, machine learning is similarly becoming an increasingly important tool to help businesses combat fraud.

In this Asia Vision Series interview on artificial intelligence, Dr Hon Hsiao-Wuen, Corporate Vice President, Microsoft Research Asia, talks about AI enabling the invisible revolution and driving a future of guardian angels.

It is no doubt that the sub-field of machine learning / artificial intelligence has increasingly gained more popularity in the past couple of years. As Big Data is the hottest trend in the tech industry at the moment, machine learning is incredibly powerful to make predictions or calculated suggestions based on large amounts of data. Some of the most common examples of machine learning are Netflix's algorithms to make movie suggestions based on movies you have watched in the past or Amazon's algorithms that recommend books based on books you have bought before. So if you want to learn more about machine learning, how do you start? For me, my first introduction is when I took an Artificial Intelligence class when I was studying abroad in Copenhagen.

In his iconic Star Wars series, George Lucas envisioned a world in a galaxy far, far away, where, among other things, doctors were droids and bots. In this world, a droid surgeon fitted Luke Skywalker with a bionic hand after a fight with Darth Vader, a bot midwife oversaw the delivery of Princess Leia and droids treated Luke Skywalker for hypothermia after his rescue from the icy planet of Hoth. Time and time again, robots, rather than humans, provided healthcare. Lucas viewed medical care as algorithmic, and therefore well within the capacity of intelligent machines. Does the world of healthcare in the Star Wars films -- where bots are the new docs -- mirror our own not-so-distant future of medicine?