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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...
114
Voted
ALT
2005
Springer
15 years 10 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...
COLT
2007
Springer
15 years 7 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
111
Voted
COLT
1993
Springer
15 years 5 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