Many tasks in machine learning and data mining, such as data diversification, non-parametric learning, kernel machines, clustering etc., require extracting a small but representative summary from a massive dataset. Often, such problems can be posed as maximizing a submodular set function subject to a cardinality constraint. We consider this question in the streaming setting, where elements arrive over time at a fast pace and thus we need to design an efficient, low-memory algorithm. One such method, proposed by Badanidiyuru et al. (2014), always finds a $0.5$-approximate solution. Can this approximation factor be improved? We answer this question affirmatively by designing a new algorithm SALSA for streaming submodular maximization. It is the first low-memory, single-pass algorithm that improves the factor $0.5$, under the natural assumption that elements arrive in a random order. We also show that this assumption is necessary, i.e., that there is no such algorithm with better than $0.5$-approximation when elements arrive in arbitrary order. Our experiments demonstrate that SALSA significantly outperforms the state of the art in applications related to exemplar-based clustering, social graph analysis, and recommender systems.

The ever-growing datasets published on Linked Open Data mainly contain encyclopedic information. However, there is a lack of quality structured and semantically annotated datasets extracted from unstructured real-time sources. In this paper, we present principles for developing a knowledge graph of interlinked events using the case study of news headlines published on Twitter which is a real-time and eventful source of fresh information. We represent the essential pipeline containing the required tasks ranging from choosing background data model, event annotation (i.e., event recognition and classification), entity annotation and eventually interlinking events. The state-of-the-art is limited to domain-specific scenarios for recognizing and classifying events, whereas this paper plays the role of a domain-agnostic road-map for developing a knowledge graph of interlinked events.

Big data is changing our lives in a big way. Use of the Internet, smart phones and many other technologies is generating 2.5 quintillion bytes of data every day. There are ever growing applications for this data, including those that could benefit your investment portfolio. In this episode of The Bid, we speak to Rich Mathieson, portfolio manager for global equity strategies and a member of the Systematic Active Equity division, about how big data is transforming the way we think about investing. Liz Koehler: The world is awash in data.

HTF Market Report is a wholly owned brand of HTF market Intelligence Consulting Private Limited. HTF Market Report global research and market intelligence consulting organization is uniquely positioned to not only identify growth opportunities but to also empower and inspire you to create visionary growth strategies for futures, enabled by our extraordinary depth and breadth of thought leadership, research, tools, events and experience that assist you for making goals into a reality. Our understanding of the interplay between industry convergence, Mega Trends, technologies and market trends provides our clients with new business models and expansion opportunities. We are focused on identifying the "Accurate Forecast" in every industry we cover so our clients can reap the benefits of being early market entrants and can accomplish their "Goals & Objectives".

The researchers collected photos of people of different races and Nao, a humanoid robot, and changed the color of the robot's shell to a variety of human skin tones. Their experimental setup relied on the "shooter bias" procedure, which has participants playing the role of a police officer who has to decide if they should or shouldn't shoot their gun when shown different images. Those photos had a person or Nao in it, either holding a weapon in their hand or some other, benign object. The study subjects saw the picture for only a split second and were asked to act on instinct. The study found that the participants were faster to shoot an armed black human and robot than they were to shoot their white counterparts.

Companies across sectors and regions are seeing an initial boost in process speed and performance from machine learning (ML). SMART MACHINES ARE REINVENTING HOW WORK IS DONE 3. To maximize the potential of AI, digital leaders must create self-adapting, self-optimizing "living processes" that use machine learning algorithms and real-time data to continuously improve. The ability for machines to act as agents of process change will unlock new roles and ways for humans and machines to work together. Of the companies surveyed: agree that machine learning will result in improvements in job satisfaction and retention. Consider your workforce and AI to be complements.

We are really pleased to announce the date of our first Meetup for the IBM PowerAI Melbourne group. Please note - this meetup is being hosted by our awesome sponsors Advent One Pty Ltd (https://www.adventone.com). Our Presenters.... Dr Adam Makarucha is a data scientist within the IBM Systems team where he is developing deep learning use cases and demonstrations for clients on IBM's PowerAI platform. He recently completed his postdoctorate at IBM Research Australia, working within the Cognitive Analytics team on deep learning applications for the financial services industry. He has worked on machine and deep learning since joining IBM in 2015, primarily focused on natural language processing as well as risk and compliance.

Sarah Jeong, a technology journalist hired by the New York Times and vilified online for tweets comparing "dumbass f****** white people" to dogs and saying they would "all go extinct soon", has been targeted for harassment by dishonest trolls, her former employer has claimed. Editors at The Verge, an online tech magazine, denounced what they called "disingenuous" criticism of Ms Jeong by "people acting in bad faith". The senior writer had been the victim of a Gamergate-style campaign designed to "divide and conquer by forcing newsrooms to disavow their colleagues", they suggested. Ms Jeong, 30, posted a string of offensive and apparently racist messages including "#CancelWhitePeople" and "white men are bulls***" up to five years ago. After being uncovered they quickly spread and were picked up by conservative media including the Daily Caller and Gateway Pundit websites.

New Zealand Prime Minister Jacinda Ardern said those are the things she has obsessed over the most as a new parent, and that the experience of focusing on such basic needs for her baby girl has helped her appreciate why people with young families may not find time for politics. "So it's our job to make sure that we are serving the needs of people, regardless of whether they have time to engage with what we're doing or not," she said. "That's something that's been really amplified for me." Ardern spoke on Thursday at her bungalow in Auckland as she prepared to return to the capital, Wellington, after six weeks of leave following the birth of her daughter, Neve. Ardern, 38, is just the second elected world leader in recent history to give birth while holding office, and her story has provided inspiration for working mothers around the world.

Often referred to as the Amazon of China, JD.com started in 1998 as a brick-and-mortar store in Beijing, but it has aspirations to be the world's leading e-commerce retailer. Based on its tremendous growth, it might not take long for the company to get there. Richard Liu, the company's founder, CEO, and chairman, has even gone so far to predict his company won't need humans and said, "I hope my company would be 100% automation someday…no human beings anymore, 100% operated by AI and robots." JD.com and its competitors such as Amazon, Alphabet, Tencent, Alibaba and more are not only racing to be the world's largest e-commerce business but to create the operating system for retail in the future. JD.com is driving business with artificial intelligence, big data, and robotics while building the retail infrastructure for the 4th industrial revolution.