Defense Advanced Research Projects AgencyTagged Content List


A process or rule set used for calculations or other problem-solving operations

Showing 53 results for Algorithms RSS
Machine learning (ML) systems today learn by example, ingesting tons of data that has been individually labeled by human analysts to generate a desired output. As these systems have progressed, deep neural networks (DNN) have emerged as the state of the art in ML models. DNN are capable of powering tasks like machine translation and speech or object recognition with a much higher degree of accuracy. However, training DNN requires massive amounts of labeled data–typically 109 or 1010 training examples. The process of amassing and labeling this mountain of information is costly and time consuming.
July 23-25, 2018,
DARPA’s Microsystems Technology Office is hosting the first annual Electronics Resurgence Initiative (ERI) Summit. The three-day event will bring together those most impacted by the coming inflection in Moore’s Law, including senior representatives from the commercial sector, defense industrial base, academia, and government, to promote collaboration and cooperation on shaping the future direction of U.S. semiconductor innovation. The event will also highlight progress and opportunities within DARPA’s ERI research programs.
Machine learning has shown remarkable success across many application areas in recent years, leveraging advances in computing power and the availability of large sets of training data. It provides a tremendous opportunity to deploy data-driven systems in more complex and interactive tasks including personalized autonomy, agile robotics, self-driving vehicles, and smart cities. Despite dramatic progress, the machine learning community still lacks an understanding of the trade-offs and mathematical limitations of related technologies for a given domain, problem, or dataset.
August 11, 2016,
George Mason University – Arlington, VA Campus (Founders Hall)
The Defense Advanced Research Projects Agency (DARPA) Microsystems Technology Office (MTO) is hosting a Proposers Day in support of the Hierarchical Identify Verify Exploit (HIVE) Program on August 11, 2016, at George Mason University – Arlington, VA Campus (Founders Hall), located at 3351 North Fairfax Drive, Arlington, VA, 22201, from 9:00 AM to 12:30 PM, Eastern Daylight Time (EDT).
June 8, 2018,
Executive Conference Center
DARPA’s Defense Sciences Office (DSO) is hosting a Proposers Day to provide information to potential proposers on the objectives of the Systematizing Confidence in Open Research and Evidence (SCORE) program. SCORE aims to develop and deploy automated tools to assign "confidence scores" to different social and behavioral science (SBS) research results and claims. Confidence scores are quantitative measures that should enable a DoD consumer of SBS research to understand the degree to which a particular claim or result is likely to be reproducible or replicable. The event will be available via a live webcast for those who would like to participate remotely.