![]() With the extra information provided in the latest data release from CMS, outside users can now investigate novel strategies on fully realistic samples, which will likely lead to exciting advances in collider data analysis.” “The performance of machine-learning techniques, however, is directly tied to the quality of the underlying training data. “Modern machine learning is having a transformative impact on collider physics, from event reconstruction and detector simulation to searches for new physics,” remarks Jesse Thaler, an Associate Professor at MIT, who is working on ML using CMS open data with two doctoral students, Patrick Komiske and Eric Metodiev. CMS has therefore also made available samples that can help foster such collaboration. According to a recent paper, collaboration with the data-science and ML community is considered a high-priority to help advance the application of state-of-the-art algorithms in particle physics. In this release, CMS open data address the ever-growing application of machine learning (ML) to challenges in high-energy physics. The new release builds upon and expands the scope of the successful use of CMS open data in research and in education. The release also includes several new data and simulation samples. With this release, which brings the volume of its open data to more than 2 PB (or two million GB), CMS has now provided open access to 100% of its research data recorded in proton–proton collisions in 2010, in line with the collaboration’s data-release policy. ![]() The CMS collaboration at CERN has released its fourth batch of open data to the public. ![]()
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