It has recently been shown that many of the existing quasi-Newton algorithms can be formulated as learning algorithms, capable of learning local models of the cost functions. Importantly, this understanding allows us to safely start assembling probabilistic Newton-type algorithms, applicable in situations where we only have access to noisy observations of the cost function and its derivatives. This is where our interest lies. We make contributions to the use of the non-parametric and probabilistic Gaussian process models in solving these stochastic optimisation problems. Specifically, we present a new algorithm that unites these approximations together with recent probabilistic line search routines to deliver a probabilistic quasi-Newton approach. We also show that the probabilistic optimisation algorithms deliver promising results on challenging nonlinear system identification problems where the very nature of the problem is such that we can only access the cost function and its derivative via noisy observations, since there are no closed-form expressions available.

We consider machine learning in a comparison-based setting where we are given a set of points in a metric space, but we have no access to the actual distances between the points. Instead, we can only ask an oracle whether the distance between two points $i$ and $j$ is smaller than the distance between the points $i$ and $k$. We are concerned with data structures and algorithms to find nearest neighbors based on such comparisons. We focus on a simple yet effective algorithm that recursively splits the space by first selecting two random pivot points and then assigning all other points to the closer of the two (comparison tree). We prove that if the metric space satisfies certain expansion conditions, then with high probability the height of the comparison tree is logarithmic in the number of points, leading to efficient search performance. We also provide an upper bound for the failure probability to return the true nearest neighbor. Experiments show that the comparison tree is competitive with algorithms that have access to the actual distance values, and needs less triplet comparisons than other competitors.

As 2016 rounded off, the year marked a significant economic increase in construction projects. Within the first 10 months, the US Census Bureau reported... A few weeks ago we got in contact with DRL, the premier drone racing league. They offered to let us ask some questions about... So you have noticed Drone Racing has been getting popular recently.

One of the main arguments the Israeli historian Yuval Noah Harari makes in Sapiens: A Brief History of Humankind is that mankind differs from other species because we can cooperate flexibly in large numbers, united in cause and spirit not by anything real, but by the fictions of our collective imagination. Examples of these fictions include gods, nations, money, and human rights, which are supported by religions, political structures, trade networks, and legal institutions, respectively. As an entrepreneur, I'm increasingly appreciative of and fascinated by the power of collective fictions. Building a technology company is hard. Lost deals, fragile egos, impulsive choices, bugs in the code, missed deadlines, frantic sprints to deliver on customer requests, the doldrums of execution, any number of things can temper the initial excitement of starting a new venture. Mission is another fiction required to keep a team united and driven when the proverbial shit hits the fan.

Two-thirds of large UK firms were targeted by cybercriminals in 2016. As the number of attacks continues to rise, what skills will the next generation of professionals need to protect us from AI hackers, rogue self-driving cars and financial ruin? The global cost of cybercrime is predicted to reach £4.9 trillion annually by 2021 and new cybersecurity trends are emerging. To fight future threats, society must develop the next generation of cyber skills. But how do businesses identify weaknesses in their cybersecurity before they're hacked?

Dr Cédric Villani, director of Pierre and Marie Curie University's Institut Henri Poincaré and recipient of the Fields Medal, gave a talk about Henri Poincaré at the Faculty of Mathematics and Physics, University of Ljubljana.

WhatsApp is going to start testing a peer-to-peer payment system this year, according to a new report. The messaging app is expected to roll the feature out to users in India in the next six months, as that's its biggest market. WhatsApp hasn't confirmed or denied the reports, which come shortly after co-founder Brian Acton hinted that such functionality was in development. The I.F.O. is fuelled by eight electric engines, which is able to push the flying object to an estimated top speed of about 120mph. The giant human-like robot bears a striking resemblance to the military robots starring in the movie'Avatar' and is claimed as a world first by its creators from a South Korean robotic company Waseda University's saxophonist robot WAS-5, developed by professor Atsuo Takanishi and Kaptain Rock playing one string light saber guitar perform jam session A man looks at an exhibit entitled'Mimus' a giant industrial robot which has been reprogrammed to interact with humans during a photocall at the new Design Museum in South Kensington, London Electrification Guru Dr. Wolfgang Ziebart talks about the electric Jaguar I-PACE concept SUV before it was unveiled before the Los Angeles Auto Show in Los Angeles, California, U.S The Jaguar I-PACE Concept car is the start of a new era for Jaguar.

Computers used to require entire buildings to operate. Now they fit in our pockets. Similarly, factory-size electronics manufacturing is approaching a contraction. Look at that $50 printer on your desk and imagine, instead of using it to spit out a hard copy of that thank-you note, that you used it to print some digital memory. Not enough memory to power a laptop. Think smaller, like smart tags to inventory all the crap in your workshop.

Hundreds of companies are incorporating artificial intelligence (AI) into their technologies to predict, prevent and defeat the next major cyber attack. At RSA last month IBM joined the pack, announcing Watson for Cyber Security and demonstrating the huge potential for artificial intelligence to support the infosec community. With internet crime growing at the rate it is, businesses need all the help they can get. According to PwC, the number of security incidents across all industries rose by 38% in 2015. See also: Where does machine learning fit in the education sector?

Darktrace's "digital antibodies" have stopped one Brexit-themed data protection threat: while trialling the machine-learning anti-hacking system's latest security automation tool, one company was alerted to an insider threat. A previously well-behaved employee reacted angrily to their employers' strategy for dealing with Brexit by digging out confidential documents with the aim of leaking them, but the would-be Julian Assange was spotted by Darktrace's Antigena, which not only uses machine learning to hunt for threats but also automates the response. "It's an interesting example, not because of Brexit, but because this staffer never leaked anything in the past," Dave Palmer, DarkTrace's director of technology tells WIRED – making such a threat hard for human colleagues to spot. "The documents were blocked from leaving the organisation." The British cybersecurity startup uses machine learning to hunt for odd behaviour on corporate systems, meaning its Enterprise Immune System can spot zero-days and other hard to find attacks.