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95
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ICML
2002
IEEE
16 years 1 months ago
Multi-Instance Kernels
Learning from structured data is becoming increasingly important. However, most prior work on kernel methods has focused on learning from attribute-value data. Only recently, rese...
Adam Kowalczyk, Alex J. Smola, Peter A. Flach, Tho...
ICML
2000
IEEE
16 years 1 months ago
Behavioral Cloning of Student Pilots with Modular Neural Networks
This paper investigates how behavioral cloning can be used to decrease training time for students learning to y on simulators. The challenges presented to each student must be tai...
Charles W. Anderson, Bruce A. Draper, David A. Pet...
ALT
2005
Springer
15 years 9 months ago
Learnability of Probabilistic Automata via Oracles
Efficient learnability using the state merging algorithm is known for a subclass of probabilistic automata termed µ-distinguishable. In this paper, we prove that state merging alg...
Omri Guttman, S. V. N. Vishwanathan, Robert C. Wil...
90
Voted
COLT
2007
Springer
15 years 6 months ago
How Good Is a Kernel When Used as a Similarity Measure?
Recently, Balcan and Blum [1] suggested a theory of learning based on general similarity functions, instead of positive semi-definite kernels. We study the gap between the learnin...
Nathan Srebro
COLT
1993
Springer
15 years 4 months ago
Lower Bounds on the Vapnik-Chervonenkis Dimension of Multi-Layer Threshold Networks
We consider the problem of learning in multilayer feed-forward networks of linear threshold units. We show that the Vapnik-Chervonenkis dimension of the class of functions that ca...
Peter L. Bartlett