Open Access. Powered by Scholars. Published by Universities.®
Physical Sciences and Mathematics Commons™
Open Access. Powered by Scholars. Published by Universities.®
- Discipline
Articles 1 - 4 of 4
Full-Text Articles in Physical Sciences and Mathematics
Intrinsic Complexity Of Learning Geometrical Concepts From Positive Data, Sanjay Jain, Efim Kinber
Intrinsic Complexity Of Learning Geometrical Concepts From Positive Data, Sanjay Jain, Efim Kinber
School of Computer Science & Engineering Faculty Publications
Intrinsic complexity is used to measure the complexity of learning areas limited by broken-straight lines (called open semi-hulls) and intersections of such areas. Any strategy learning such geometrical concepts can be viewed as a sequence of primitive basic strategies. Thus, the length of such a sequence together with the complexities of the primitive strategies used can be regarded as the complexity of learning the concepts in question. We obtained the best possible lower and upper bounds on learning open semi-hulls, as well as matching upper and lower bounds on the complexity of learning intersections of such areas. Surprisingly, upper …
On The Intrinsic Complexity Of Learning Recursive Functions, Sanjay Jain, Efim Kinber, Christophe Papazian, Carl Smith, Rolf Wiehagen
On The Intrinsic Complexity Of Learning Recursive Functions, Sanjay Jain, Efim Kinber, Christophe Papazian, Carl Smith, Rolf Wiehagen
School of Computer Science & Engineering Faculty Publications
The intrinsic complexity of learning compares the difficulty of learning classes of objects by using some reducibility notion. For several types of learning recursive functions, both natural complete classes are exhibited and necessary and sufficient conditions for completeness are derived. Informally, a class is complete iff both its topological structure is highly complex while its algorithmic structure is easy. Some self-describing classes turn out to be complete. Furthermore, the structure of the intrinsic complexity is shown to be much richer than the structure of the mind change complexity can behave “orthogonally”.
On Learning Of Functions Refutably, Sanjay Jain, Efim Kinber, Rolf Wiehagen, Thomas Zeugmann
On Learning Of Functions Refutably, Sanjay Jain, Efim Kinber, Rolf Wiehagen, Thomas Zeugmann
School of Computer Science & Engineering Faculty Publications
Learning of recursive functions refutably informally means that for every recursive function, the learning machine has either to learn this function or to refute it, that is to signal that it is not able to learn it. Three modi of making precise the notion of refuting are considered. We show that the corresponding types of learning refutably are of strictly increasing power, where already the most stringent of them turns out to be of remarkable topological and algorithmical richness. Furthermore, all these types are closed under union, though in different strengths. Also, these types are shown to be different with …
Ethical Issues In Open Source Software, Frances Grodzinsky, Keith W. Miller, Marty J. Wolf
Ethical Issues In Open Source Software, Frances Grodzinsky, Keith W. Miller, Marty J. Wolf
School of Computer Science & Engineering Faculty Publications
In this essay we argue that the current social and ethical structure in the Open Source Software (OSS) Community stem from its roots in academia. The individual developers experience a level of autonomy similar to that of a faculty member. Furthermore, we assert that the Open Source Software Community's social structure demands benevolent leadership. We argue that it is difficult to pass off low quality open source software as high quality software and that the Open Source development model offers strong accountability. Finally, we argue that Open Source Software introduces ethical challenges for universities and the software development community.