COPYRIGHT YEAR

2009

AUTHORS

Shai Ben-David

TITLE

Theory-Practice Interplay in Machine Learning – Emerging Theoretical Challenges

ABSTRACT

Theoretical analysis has played a major role in some of the most prominent practical successes of statistical machine learning. However, mainstream machine learning theory assumes some strong simplifying assumptions which are often unrealistic. In the past decade, the practice of machine learning has led to the development of various heuristic paradigms that answer the needs of a vastly growing range of applications. Many useful such paradigms fall beyond the scope of the currently available analysis. Will theory play a similar pivotal role in the newly emerging sub areas of machine learning? In this talk, I will survey some such application-motivated theoretical challenges. In particular, I will discuss recent developments in the theoretical analysis of semi-supervised learning, multi-task learning, “learning to learn”, privacy-preserving learning and more.

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25 TRIPLES      25 PREDICATES      20 URIs      11 LITERALS

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1 book-chapters:698eefd92e5a41da4caf76c581253cc3 sg:abstract Abstract Theoretical analysis has played a major role in some of the most prominent practical successes of statistical machine learning. However, mainstream machine learning theory assumes some strong simplifying assumptions which are often unrealistic. In the past decade, the practice of machine learning has led to the development of various heuristic paradigms that answer the needs of a vastly growing range of applications. Many useful such paradigms fall beyond the scope of the currently available analysis. Will theory play a similar pivotal role in the newly emerging sub areas of machine learning? In this talk, I will survey some such application-motivated theoretical challenges. In particular, I will discuss recent developments in the theoretical analysis of semi-supervised learning, multi-task learning, “learning to learn”, privacy-preserving learning and more.
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6 sg:copyrightHolder Springer-Verlag Berlin Heidelberg
7 sg:copyrightYear 2009
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9 sg:doi 10.1007/978-3-642-04180-8_1
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15 sg:language En
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17 sg:metadataRights OpenAccess
18 sg:pageFirst 1
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20 sg:scigraphId 698eefd92e5a41da4caf76c581253cc3
21 sg:title Theory-Practice Interplay in Machine Learning – Emerging Theoretical Challenges
22 sg:webpage https://link.springer.com/10.1007/978-3-642-04180-8_1
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24 rdfs:label BookChapter: Theory-Practice Interplay in Machine Learning – Emerging Theoretical Challenges
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