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Data Science News
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Tweet of the Week
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Twitter, I Will Block Ya Mama
from October 27, 2016
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Prof works to develop interactive robotic assistant
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Brown University, Brown Daily Herald
from October 27, 2016
While interactive robots have been popularized by science fiction over the past century, Assistant Professor of Computer Science Stefanie Tellex and her research group are working to make them a reality. By focusing on robotic language, perception and action, Tellex hopes to create a robot that can assist humans in both simple and complex tasks.
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[1610.08613] Can Active Memory Replace Attention?
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arXiv, Computer Science > Learning; Łukasz Kaiser, Samy Bengio
from October 27, 2016
“So far, however, active memory has not improved over attention for most natural language processing tasks, in particular for machine translation. We analyze this shortcoming in this paper and propose an extended model of active memory that matches existing attention models on neural machine translation and generalizes better to longer sentences. We investigate this model and explain why previous active memory models did not succeed. Finally, we discuss when active memory brings most benefits and where attention can be a better choice.”
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Stanford Professor Analyzes Everyday Influence of Linguistics
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The Cornell Daily Sun
from October 22, 2016
Prof. Daniel Jurafsky, linguistics and computer science, Stanford University, described the unexpected role linguistics play in the construction of restaurant menus and police-civilian interactions at a lecture Thursday.
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Biologist recruits USC researcher to study cancer — her own
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USC News
from October 24, 2016
After Shirley Pepke was diagnosed with ovarian cancer, she had trouble finding information she needed — so she and USC physicist and data expert Greg Ver Steeg got to work.
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A New Kind of AI: Google’s Deep Learning Neural Nets Have Learned Encryption
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Futurism, Dom Galeon
from October 27, 2016
Over a course of 15,000 tries, Google researches were about to create neural networks that could successfully write and decode a cipher that a third party could not.
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Why More Students are Getting Data Science Degrees Online
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Media Planet, Education and Career News, Columbia Engineering
from October 27, 2016
In an increasingly data-driven world, students are learning to harness the power of data through a new online course that complements Columbia’s existing data science programs.
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Giant Genetic Map Shows Life’s Hidden Links
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Quanta Magazine, Veronique Greenwood
from October 25, 2016
In a monumental set of experiments, spread out over nearly two decades, biologists removed genes two at a time to uncover the secret workings of the cell.
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Computational Biology: De-risking startups while still doing big science.
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Vijay Pande is a former Stanford professor, known for his Folding At Home distributed computing effort in computational structural biology. Now Pande is a Silicon Valley venture capitalist and he’s identified three areas where software approaches and machine learning can have health impacts via biology: digital therapeutics, cloud biology and computational medicine. Compared to biotech investing, software de-risks healthcare technology, Pande says. He adds, there’s also a new generation of computational biology founders who are A+ in life science and A+ in computing, something that required two separate people not long ago. View the 13 minute video interview with Pande at the Andreessen Horowitz venture firm’s website.
De-risking was probably less of a factor in the big science computational biology programs that are reporting results, something that Veronique Greenwood reports on in Quanta Magazine. It’s also good to hear about new efforts to undertake long-term, longitudinal big science computational biology, like BabySeq, which will do at-birth genome sequencing.
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As Artificial Intelligence Evolves, So Does Its Criminal Potential
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The New York Times
from October 23, 2016
“The thing people don’t get is that cybercrime is becoming automated and it is scaling exponentially,” said Marc Goodman, a law enforcement agency adviser and the author of Future Crimes. He added, “This is not about Matthew Broderick hacking from his basement,” a reference to the 1983 movie “War Games.”
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Hacking Harvard open data to fight crime, save energy, and improve student life
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Medium, Harvard Open Data Project, Athena Kan
from October 27, 2016
Our ultimate goals are to convince Harvard to start standardizing and organizing its data and to empower Harvard students and community members to make powerful apps, services, and policies with this data.
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Deadlines
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NOT-OD-17-009: Notice of Extension of the Response Date for NOT-OD-17-006 “Including Preprints and Interim Research Products in NIH Applications and Reports”
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deadline: RFP
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This Notice extends the response date for NOT-OD-17-006 “Request for information (RFI): Including Preprints and Interim Research Products in NIH Applications and Reports”. Deadline to respond is Friday, December 9.
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NYU Center for Data Science News
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Graduate Study in Data Science Open House
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NYU Center for Data Science
from October 28, 2016
If you would like to learn more about the PhD in Data Science program and are in the NYC area, please plan to attend our Open House below. The Open House provides an overview of the doctoral program and gives you a chance to interact with faculty and staff at the NYU Center for Data Science.
Thursday, November 10, 2016
6:00pm-7:00pm
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Tools & Resources
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A Quantum Leap for the Web
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Medium, Mozilla Tech
from October 27, 2016
Over the past year, our top priority for Firefox was the Electrolysis project to deliver a multi-process browsing experience to users. Running Firefox in multiple processes greatly improves security and performance. This is the largest change we’ve ever made to Firefox, and we’ll be rolling out the first stage of Electrolysis to 100% of Firefox desktop users over the next few months.
But, that doesn’t mean we’re all out of ideas in terms of how to improve performance and security. In fact, Electrolysis has just set us up to do something we think will be really big.
We’re calling it Project Quantum.
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Using R to Forecast Sentiment Analysis
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Algorithmia
from October 27, 2016
We want to teach how to integrate this into your R project and build a pipeline for forecasting the sentiment of a time series using the Forecast algorithm. Forecasting sentiment time series data is useful when there is a seasonal component in a variety of use cases such as scheduling call center employees for a retail business, understanding market sentiment for stock market prediction or adjusting your social media marketing campaigns based on sentiment forecasts.
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Careers
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Tenured and tenure track faculty positions |
Assistant, Associate, or Full Professor, Biology
University of Oregon; Eugene, OR
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Faculty Positions in the Department of Computer Science
Columbia University; New York, NY
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