We present a predictive analysis model for 2019 men's Cricket World Cup. We believe this predictive analysis strategy would be very useful for viewers, sponsors, and team strategists. This would also give insights to various cricket analysts and commentators about the features that play a crucial role in the statistical analysis. This model is developed based on the historical data collected for the 10 participating teams (Afghanistan, Australia, Bangladesh, England, India, New Zealand, Pakistan, South Africa, Sri Lanka, and West Indies). In addition, we test our model on 2015 world cup data and measure the accuracy of predictions.

The Azeri-Chirag-Deepwater Gunashli (ACG), a sprawling complex of offshore oil fields 60 miles off Azerbaijan's capital Baku, is causing somewhat of a headache for BP's head of technology. "We have huge production in Azerbaijan of wells that are quite prone to producing sand, and sand if it's produced in high quantities from our oil wells can do damage to the metalwork and also choke back the production," says David Eyton. The ACG, which pumps out an average of 584,000 barrels of oil per day, is a prized asset for BP, and any hold ups could cost the company dearly. But the man leading BP's technology revolution think he has a solution: artificial intelligence (AI).

Washington says Huawei could be compelled by Beijing to spy on or disable foreign telecom networks that use its equipment. The Trump administration has been particularly focused on dissuading allies from using Huawei gear in their rollout of 5G--the next-generation mobile networks that promise to connect more things, including self-driving cars and factory components, to the internet. In a sign of the challenges ahead for U.S. officials, though, the trade show here has offered Huawei the opportunity to tout new deals with America's friends. It used this week's Mobile World Congress, rebranded this year as MWC Barcelona, to announce a high-profile agreement with the biggest carrier in the United Arab Emirates, one of America's closest Mideast allies, to build that country's first 5G network. Despite facing off on European soil, Huawei is benefiting from the sense of a home-court advantage here.

The fundraising round was led by South Korean chip maker SK Hynix Inc and several "first-tier" Chinese automakers, while other participants included China Oceanwide Capital, Citic Securities' One-Belt-One-Road Fund, and Minsheng Capital, Horizon said in a statement on its website.

As any creative will know, a significant amount of time is spent on the discovery process, researching and experimenting. This is where AI is poised to make a significant impact, especially when it comes to advertising. For example, companies like Tel Aviv-based Bidalgo, an AI-powered ad automation platform, offer a repository of creative that is continuously uploaded and A/B tested. It uses machine learning for image and video recognition to break down the different variables such as concept and copy, with a view to finding out why we like what we like when it comes to designing future ad creative.

Australian video scale-up Oovvuu has closed a second funding round, raising $4.8 million to drive its global expansion. The company uses proprietary artificial intelligence to read publishers' articles, watch broadcasters' videos and match them together, with the goal of putting relevant news video in every article in the world. Since launching in 2014, the company has partnered with 100 global broadcasters and publishers including The BBC, Reuters, Bloomberg, Agence France Presse, Associated Press and Australia's Seven West Media. Led by Cygnet Capital, the $4.8 million round was heavily oversubscribed and underpinned by institutional investors including Regal Funds Management. It follows Cygnet's initial $3.7 million investment in Oovvuu in early 2018.

A lack of skilled workers is stopping many Asian companies from embracing artificial intelligence, according to a new study by Microsoft and International Data Corporation. While artificial intelligence (AI) is expected to speed up innovation in the Asia Pacific region over the next few years, only 41% of companies in the region are currently using the technology, according to a recent Microsoft and International Data Corporation survey of business leaders and workers in 15 Asia Pacific countries. One of the main obstacles preventing companies in the region from embracing AI is a skills shortage, the study found. The report highlighted the fact that while a majority of companies say they are willing to invest and retrain workers, many lacked time and an understanding of where to start. China has launched an aggressive campaign to dominate the AI space through public and private investments into the technology, aiming to be a world leader in AI innovation by 2030.

Fifteen years ago I came to Bangalore, India's Silicon Valley, to do a documentary on outsourcing. One of our first stops was a company called 24/7 whose main business was answering customer service calls and selling products, like credit cards, for U.S. companies half a world away. The beating heart of 24/7 back then was a vast floor of young phone operators, most with only high school degrees, save for a small pool of techies who provided "help desk" advice. These young Indians spoke in the best American English, perfected in a class that we filmed, where everyone had to practice enunciating "Peter Piper picked a peck of pickled peppers" -- and make it sound like they were from Kansas not Kolkata. The operations floor was so noisy from hundreds of simultaneous phone conversations that 24/7 installed a white-noise machine to muffle the din, but even then you could still occasionally hear piercing through the cacophony some techie saying to someone in America, the likes of: "What, Ma'am? Your computer is on fire?"

We study the problem of stochastic combinatorial pure exploration (CPE), where an agent sequentially pulls a set of single arms (a.k.a. a super arm) and tries to find the best super arm. Among a variety of problem settings of the CPE, we focus on the full-bandit setting, where we cannot observe the reward of each single arm, but only the sum of the rewards. Although we can regard the CPE with full-bandit feedback as a special case of pure exploration in linear bandits, an approach based on linear bandits is not computationally feasible since the number of super arms may be exponential. In this paper, we first propose a polynomial-time bandit algorithm for the CPE under general combinatorial constraints and provide an upper bound of the sample complexity. Second, we design an approximation algorithm for the 0-1 quadratic maximization problem, which arises in many bandit algorithms with confidence ellipsoids. Based on our approximation algorithm, we propose novel bandit algorithms for the top-k selection problem, and prove that our algorithms run in polynomial time. Finally, we conduct experiments on synthetic and real-world datasets, and confirm the validity of our theoretical analysis in terms of both the computation time and the sample complexity.

The $\ell_p$ linear regression problem is to minimize $f(x)=||Ax-b||_p$ over $x\in\mathbb{R}^d$, where $A\in\mathbb{R}^{n\times d}$, $b\in \mathbb{R}^n$, and $p>0$. To avoid overfitting and bound $||x||_2$, the constrained $\ell_p$ regression minimizes $f(x)$ over every unit vector $x\in\mathbb{R}^d$. This makes the problem non-convex even for the simplest case $d=p=2$. Instead, ridge regression is used to minimize the Lagrange form $f(x)+\lambda ||x||_2$ over $x\in\mathbb{R}^d$, which yields a convex problem in the price of calibrating the regularization parameter $\lambda>0$. We provide the first provable constant factor approximation algorithm that solves the constrained $\ell_p$ regression directly, for every constant $p,d\geq 1$. Using core-sets, its running time is $O(n \log n)$ including extensions for streaming and distributed (big) data. In polynomial time, it can handle outliers, $p\in (0,1)$ and minimize $f(x)$ over every $x$ and permutation of rows in $A$. Experimental results are also provided, including open source and comparison to existing software.