Computer Science and Applied Mathematics

On Learning
Zhou Zhi-Hua, National Key Lab for Novel Software Technology, Nanjing University

“Machine learning” studies the design, analysis and application of algorithms that are able to construct a model, such as a classifier, from historical data. With machine learning techniques, given a set of “training examples”, i.e., samples with known outputs, one can expect to generate a model that may often be able to work well on unseen data. Thus, machine learning techniques can be helpful in any fields that require data analysis. With the rapid accumulation of data, both in scientific research or in daily life, the requirement of data analysis with computing machines becomes more and more demanding, and therefore, machine learning research and applications have experienced an explosive development during the past decade. In this talk, we will give a brief introduction to machine learning, including its history, state-of-the-art techniques, applications and some challenges.

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Computer Science and Applied Mathematics

Kavli Frontiers of Science PRO

The Kavli Frontiers of Science symposium series is the National Academy of Science’s premiere activity for distinguished young scientists. Unlike meetings that focus on a narrow area of science, these meetings allow participants to explore innovative


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The Kavli Frontiers of Science symposium series is the National Academy of Science’s premiere activity for distinguished young scientists. Unlike meetings that focus on a narrow area of science, these meetings allow participants to explore innovative research ideas across a wide variety of fields and to develop new networks that will serve them as they progress in their careers..

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