Data Science newsletter – September 13, 2018

GROUP CURATION: N/A

Federal regulators are cracking down on sales of deadly illegal drugs on social marketing platforms, a problem pointed out by the researcher.

Vice Provost Kaushik Bhattacharya notes that “high-performance computing has become a ubiquitous tool in all areas of science and engineering. This facility eliminates the barrier to entry and enables Caltech researchers to focus on the core research issues in an HPC environment without having to maintain their own systems.” … Funded by the Office of the Provost and a $2 million grant from the Moore Foundation, the HPC Center boasts nearly 7,500 CPU cores and 200 NVidia P100 graphics-processing units. I

Model from MIT Lincoln Laboratory Intelligence and Decision Technologies Group sets a new standard for understanding how a neural network makes decisions.

Engineers have developed a way for a robot arm to visually study just a handful of different shoes, craning itself back and forth like a snake to get a good look at all the angles. Then when the researchers drop a different, unfamiliar kind of shoe in front of the robot and ask it to pick it up by the tongue, the machine can identify the tongue and give it a lift—without any human guidance. They’ve taught the robot to fish for, well, boots, like in the cartoons. And that could be big news for robots that are still struggling to get a grip on the complicated world of humans.

MIT Sloan professor Roberto Rigobon and Harvard University professor Alberto Cavallo are the co-founders of the Billion Prices Project. The project collects prices — it has around 15 million prices today — provided by online retailers around the world. The public data is used to conduct research in macroeconomics and international economics. The professors say there are many ways to measure life, and they’re helping fellow researchers access the data to do it.

UC Berkeley is launching a new form of collaboration that links students, government, community, and business partners to leverage data to help address complex social problems, from access to safe drinking water to disaster recovery to affordable housing.

The Data Collaboratives program, created with founding support from Schmidt Futures (link is external), will provide opportunities for student-driven innovations emerging in UC Berkeley’s thriving data science community to grow into broader collaborations for positive social impact.

“UC Berkeley is an ideal campus for this initiative – given its expertise in data science, deep commitment to tackling hard societal problems, and entrepreneurial students,” said Tom Kalil, Chief Innovation Officer of Schmidt Futures. “I hope philanthropists, non-profits, government agencies, and companies will join with us to support this effort, and unlock the potential of data science to help solve our most pressing challenges.”

The National Science Foundation (NSF) has awarded funding to 18 cross-disciplinary projects to conduct innovative research on neural and cognitive systems.

The awards contribute to NSF’s investments in support of Understanding the Brain and the BRAIN Initiative, a coordinated research effort that seeks to accelerate the development of new neurotechnologies.

“The teams will integrate multiple disciplines to look at fundamental questions about the brain in new ways,” said Shubhra Gangopadhyay, NSF program director in the Engineering Directorate. “The research will tackle problems that were previously intractable for neuroscience and cognitive science and will open up new avenues for future research. We are excited to see where these high-risk, high-reward proposals take us as a field.”

Matthew Guzdial and Mark Riedl, researchers from Georgia Tech’s School of Interactive Computing recently pre-published a paper titled “Automated Game Design via Conceptual Expansion,” which they believe lays the groundwork for creating one.

The conceptual expansion algorithms work by taking input in the form of video game levels from already developed games and converting them into an output that lays out the environments, objects, and rules for a new video game.

Automated game design has remained a key challenge within the field of Game AI. In this paper, we introduce a method for recombining existing games to create new games through a process called conceptual expansion. Prior automated game design approaches have relied on hand-authored or crowd-sourced knowledge, which limits the scope and applications of such systems. Our approach instead relies on machine learning to learn approximate representations of games. Our approach recombines knowledge from these learned representations to create new games via conceptual expansion. We evaluate this approach by demonstrating the ability for the system to recreate existing games. To the best of our knowledge, this represents the first machine learning-based automated game design system.

A team from Georgia Tech has received an award for $3.7 million from the National Science Foundation to cover 70 percent of the cost of a new high performance computing (HPC) resource for the upcoming Coda building’s data center.

The El Niño/La Niña pattern in the Pacific Ocean is notorious for its long-distance effects on weather as far away as Africa and the Midwestern United States. But climate experts also know of several other such patterns, known as “teleconnections,” and believe that there are many more to be discovered.

The new TRIPODS+Climate project, a collaboration among the University of Chicago, University of Wisconsin-Madison and the University of California-Irvine, will develop novel data science tools to sniff out these hidden patterns, improving weather forecasts and scientific understanding of global climate. Researchers will apply data science methods such as machine learning, network analysis and predictive modeling to the growing flood of climate data.

The University of Minnesota announced today that it has received a three-year, $1.43 million grant from the National Science Foundation to advance machine learning techniques to better monitor global agricultural and environmental change—a practice that can help society address the challenges of adapting to a changing climate, managing land use and natural resources, and sustainably feeding a growing population.

Computer scientist Abhradeep Guha Thakurta has won NSF funding to investigate ways to protect the privacy of individuals while allowing access to large genomic data sets

University System of Georgia officials announced Tuesday they’re starting a hub at Georgia State University’s Robinson College of Business for all 26 colleges and universities in the system to learn and train more students for careers in the financial technology industry, saying there’s a labor gap in the state.

The initiative, FinTech Academy, will be a public-private partnership with businesses that will cost about $20 million over the next three years. University System officials said they’ll reallocate some funds for the effort. One company, FIS, a banking software and services company located in more than 100 countries, announced Tuesday it’s committing $1 million to the academy.

New York, NY Wednesday, September 19, starting at 6:30 p.m., NYC Data Science Academy (500 8th Ave, Suite 905). “Dataiku, ACM and NYC Data Science Academy are hosting two talks focused on human influence in data science.” [free, rsvp required]

Berkeley, CA September 20 starting at 5:30 p.m., Geballe Room, Townsend Center, 220 Stephens Hall, UC Berkeley. “Andrew Piper is a Professor and William Dawson Scholar in the Department of Languages, Literatures, and Cultures at McGill University. He directs .txtLAB, a digital humanities laboratory at McGill.” [free]

” Today, we are launching the What-If Tool, a new feature of the open-source TensorBoard web application, which let users analyze an ML model without writing code. Given pointers to a TensorFlow model and a dataset, the What-If Tool offers an interactive visual interface for exploring model results.”

Starting with: “Zero-Shot Transfer with Deictic Object-Oriented Representation in Reinforcement Learning” by Ofir Marom and Benjamin Rosman.