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Data Science News
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Medium’s Publishing API
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Medium
from October 08, 2015
With our Publishing API, you can now share your story on Medium from anywhere. It’s easier than ever to plug into our network and build your audience here. There are so many amazing stories, ideas, and perspectives shared here every day, and we want to make reading on Medium even better, with more avenues for content creators of all shapes and sizes.
For those who’ve already started things of your own, the Medium Publishing API gives you an easy way to share your content here too.
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Machine Learning in the World of Sports – Rajiv Maheswaran
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YouTube, O'Reilly
from October 08, 2015
Second Spectrum CEO Rajiv Maheswaran talks at Strata+Hadoop on the beginnings of machine learning in the world of professional sports.
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Data Science Education: Where It Needs To Begin
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KDnuggets, Feyzi Bagirov
from October 08, 2015
Most data science education centers on graduate degrees, with only 14 US undergraduate analytics degrees in 2014. With the vast amounts of data being generated, should there be more data science education at the undergraduate level?
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direct and indirect effects of “citation padding” « scatterplot
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scatterplot blog, Jeremy Freese
from October 08, 2015
Phil [Cohen] has had a couple of posts now about the practice of journal editors encouraging citations to a journal that they edit, and it sounds like there may be more. I should say that I don’t recall ever having an editor say something as… direct as the statement Phil quotes, and I do remember being on projects where, on our own initiative, we’ve inserted references to a journal or the work of its editor with “can’t hurt our chances!” rationale.
One might think the specific practice of editors encouraging citations to their journal for impact-factor purposes could be curbed by simply eliminating journal-level self-citations from impact factor counts. But: my suspicion is that when people insert citations in with the idea of pleasing editors at a specific journal, they mostly don’t bother to remove those citations if the paper gets rejected from the journal anyway.
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Differential Privacy: Safely Sharing and Studying Sensitive Data
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Scientific Computing, National Science Foundation
from October 08, 2015
The promise of big data lies in researchers’ ability to mine massive datasets for insights that can save lives, improve services and inform our understanding of the world. These data may be generated by surfing the Web, interacting with medical devices or passing sensors. Some data may be trivial, but in many cases, data are deeply personal. They can even influence our insurance premiums or the price we pay for a product online.
When planning a study, data scientists need to balance their desire to uncover new knowledge with the privacy of the people whom the data represent.
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The summer of data science – Microsoft Research Connections Blog – Site Home – MSDN Blogs
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Microsoft Research Connections Blog
from October 08, 2015
While we live and breathe data science year-round at Microsoft Research, this summer, we offered a broad range of data science education opportunities for young researchers. Participation in these events was extremely rewarding—for both the students and the organizers.
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CRN | Ph.D. recipients in computing fields are primarily non-U.S. residents in most states in the U.S.
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Computing Research Association
from October 01, 2015
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Events
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Conference on Responsible Use of Open Data: Government and the Private Sector
The Conference on Responsible Use of Open Data: Government and the Private Sector, to be held at New York University on November 19-20, 2015 is co-organized by BCLT and NYU’s Information Law Institute and Department of Media, Culture and Communication. The event continues and expands the issues addressed by the April 2015 BCLT event Open Data: Addressing Privacy, Security, and Civil Rights Challenges Symposium. We are delighted that Dr. Amen Ra Mashariki, the City of New York Chief Analytics Officer and in charge of the Mayor’s Office of Data Analytics has agreed to open the conference in the afternoon of November 19th. Registration is required.
Thursday-Friday, November 19-20, at NYU School of Law
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Deadlines
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The Allen AI Science Challenge
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deadline: subsection?
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The Allen Institute for Artificial Intelligence (AI2) is working to improve humanity through fundamental advances in artificial intelligence. One critical but challenging problem in AI is to demonstrate the ability to consistently understand and correctly answer general questions about the world. … Using a dataset of multiple choice question and answers from a standardized 8th grade science exam, AI2 is challenging you to create a model that gets to the head of the class.
Started: 4:13 pm, Wednesday 7 October 2015 UTC
Ends: 11:59 pm, Saturday 13 February 2016 UTC (129 total days)
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CDS News
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New Study Raises Questions about Training by Repetition for Those With Autism
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New York University
from October 06, 2015
Training individuals with autism spectrum disorder (ASD) to acquire new information by repeating the information may harm their ability to apply that learned knowledge to other situations, a study by a team of neuroscientists shows.
This finding, published in the journal Nature Neuroscience, challenges the popular educational approaches designed for ASD individuals that focus on repetition and drills. It has been thought that because those with ASD sometimes acquire a new behavior or skill only in a specific context, and have difficulty transferring that learned skill or information to a new context, repetition can aid the learning process.
“Our conclusion is quite different: breaks in repetition allow the visual system some time to rest and allow autistic individuals to learn efficiently and to then generalize,” says David Heeger, a professor in NYU’s Center for Neural Science and one of the study’s co-authors.
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