NYU Data Science newsletter – September 30, 2015

NYU Data Science Newsletter features journalism, research papers, events, tools/software, and jobs for September 30, 2015

GROUP CURATION: N/A

 
Data Science News



The ‘Hot Hand’ Debate Gets Flipped on Its Head – WSJ

Wall Street Journal


from September 28, 2015

People have been hunting for proof of the hot hand in basketball longer than Stephen Curry has been alive. The search has lasted three decades and exhausted almost all options. But the results were usually the same. There was no evidence of the hot hand. A player who made a shot was no more likely to make his next shot.

Then something strange happened this summer. Economists, psychologists and statisticians started talking about a new paper on basketball. It claimed that the hot hand really does exist. But what made it truly mind-boggling was that the authors used the simplest scientific method: coin flips.

 

Implementing a Graduate-Level Research Data Management Course: Approach, Outcomes, and Lessons Learned

Journal of Librarianship and Scholarly Communication


from September 22, 2015

INTRODUCTION As data-driven research becomes the norm, practical knowledge in data stewardship is critical for researchers. Despite its growing importance, formal education in research data management (RDM) is rare at the university level. Academic librarians are now playing a leadership role in developing and providing RDM training and support to faculty and graduate students. This case study describes the development and implementation of a new, credit-bearing course in RDM for graduate students from all disciplines.

 

Machine Learning in Retail: Consumer Privacy Implications

Fast Forward Labs


from September 29, 2015

Many companies are working to retro-fit physical stores with capabilities originally developed for ecommerce. Without adding any new sensors or tags, image recognition company Blippar provides APIs that digitize physical products to create an in-app experience around them. Farfetch, which initially brought an exclusive network of luxury brick & mortar shops online, recently announced that it will soon provide in-store analytics.

In parallel, digital companies continue to seek out physical spaces to augment their customer experience. Warby Parker and Rent the Runway have physical stores, and Gilt and Etsy are exploring new models to engage consumers offline (Gilt has a private retail space in their corporate headquarters and Etsy launched an app to inform shoppers of sellers’ nearby products). These digital companies were built upon testing every detail affecting their website performance. As tracking migrates to physical retail, it’s important that retailers consider the consumer experience risks associated with new technologies as they explore the benefits.

 

Rise of Concerns about AI

Communications of the ACM


from September 28, 2015

By Thomas G. Dietterich, Eric J. Horvitz

Discussions about artificial intelligence (AI) have jumped into the public eye over the past year, with several luminaries speaking about the threat of AI to the future of humanity. Over the last several decades, AI—automated perception, learning, reasoning, and decision making—has become commonplace in our lives. We plan trips using GPS systems that rely on the A* algorithm to optimize the route. Our smartphones understand our speech, and Siri, Cortana, and Google Now are getting better at understanding our intentions. Machine vision detects faces as we take pictures with our phones and recognizes the faces of individual people when we post those pictures to Facebook Internet search engines rely on a fabric of AI subsystems. On any day, AI provides hundreds of millions of people with search results, traffic predictions, and recommendations about books and movies.

 

Artificial Intelligence: Comeback Chance for Japanese Manufacturing

Nippon.com


from September 30, 2015

… Aside from the above three Internet giants, we see a proliferation of start-ups that are seeking to tap the potential of advanced AI and deep learning. The United States, which won decisively in the Internet race, is maintaining its overwhelming lead in the current competition to develop AI, the key technology for the years to come. Its closest rivals at this point are Asian: China’s Baidu and Tsinghua University, Hong Kong University, and the National University of Singapore. Japan is part of the second pack, which lags far behind the leaders.

 

Of Big Data, the IoT, and Trust: Tales from Google’s Nest

SmartData Collective


from September 29, 2015

… Nest serves as a great example of an Internet of Things business which is coming up with products that have the potential to simplify or improve our lives, but accompanied by their own set of emerging problems, in terms of privacy and data security. Whether we accept them into our lives or reject them through distrust will most likely be down to how the delivery of the services is managed.

 
Events



Why Do Liberals Drink Lattes?



We are honored to host Prof. Michael Macy. Prof. Macy is the Goldwin Smith Professor of Arts and Sciences and Director of the Social Dynamics Laboratory at Cornell, with a dual appointment in the Departments of Sociology and Information Science.

Prof. Macy’s work explores familiar but enigmatic social patterns, such as circadian rhythms, lifestyle politics, the mesh of civilizations, the emergence and collapse of fads, the spread of self-destructive behaviors, cooperation in social dilemmas, the critical mass in collective action, the spread of complex contagions, the polarization of opinion, segregation of neighborhoods, and assimilation of minority cultures.

Friday, October 2, at 6 p.m., Courant Institute, NYU, 251 Mercer St.

 

WORKSHOP ON INFORMATION IN NETWORKS (WIN)



WIN is a Social Networks Summit intended to foster collaboration and to build community. The increasing availability of massive networked data is revolutionizing the scientific study of a variety of phenomena in fields as diverse as Computer Science, Economics, Physics and Sociology. Yet, while many important advances have taken place in these different communities, the dialog between researchers across disciplines is only beginning. The purpose of WIN is to bring together leading researchers studying ‘information in networks’ – its distribution, its diffusion, its value, and its influence on social and economic outcomes – in order to lay the foundation for ongoing relationships and to build a lasting multidisciplinary research community.

Friday-Saturday, October 2-3, at Stern School of Business, NYU

 

NYU Survey Service (Qualtrics) – Research Guides at New York University



The NYU Data Service provides Qualtrics, a tool for creating and administering web-based surveys for research, teaching, and administrative needs. … Data Services offers a tutorial on Survey Software several times per semester that includes an Introduction to Qualtrics Survey Design. For more information and to sign up, visit NYU Data Service’s Library Class.

Tuesday, October 6, from 11 a.m. to 3 p.m., NYU Kimmel Building, Room 914

 

Pinterest Chief Scientist Prof. Jure Leskovec: Discovering Networks of Products



In a modern recommender system, it is important to understand how products relate to each other. For example, while a user is looking for mobile phones, it might make sense to recommend other phones, but once they buy a phone, we might instead want to recommend batteries, cases, or chargers. These two types of recommendations are referred to as substitutes and complements: substitutes are products that can be purchased instead of each other, while complements are products that can be purchased in addition to each other. In this talk I will present methods for automatically identifying networks of substitute and complementary relationships of products, using text from their online reviews.

Tuesday, October 20, at 7 p.m., NetFlix in Los Gatos.

 

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