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COLT
1999
Springer
14 years 2 months ago
On PAC Learning Using Winnow, Perceptron, and a Perceptron-like Algorithm
In this paper we analyze the PAC learning abilities of several simple iterative algorithms for learning linear threshold functions, obtaining both positive and negative results. W...
Rocco A. Servedio
ICML
2000
IEEE
14 years 11 months ago
Combining Reinforcement Learning with a Local Control Algorithm
We explore combining reinforcement learning with a hand-crafted local controller in a manner suggested by the chaotic control algorithm of Vincent, Schmitt and Vincent (1994). A c...
Andrew G. Barto, Jette Randløv, Michael T. ...
ICML
2007
IEEE
14 years 11 months ago
Large-scale RLSC learning without agony
The advances in kernel-based learning necessitate the study on solving a large-scale non-sparse positive definite linear system. To provide a deterministic approach, recent resear...
Wenye Li, Kin-Hong Lee, Kwong-Sak Leung
ICML
2003
IEEE
14 years 11 months ago
Learning Metrics via Discriminant Kernels and Multidimensional Scaling: Toward Expected Euclidean Representation
Distance-based methods in machine learning and pattern recognition have to rely on a metric distance between points in the input space. Instead of specifying a metric a priori, we...
Zhihua Zhang
IUI
1999
ACM
14 years 3 months ago
Programming by Demonstration: An Inductive Learning Formulation
Although Programming by Demonstration (PBD) has the potential to improve the productivity of unsophisticated users, previous PBD systems have used brittle, heuristic, domain-speci...
Tessa A. Lau, Daniel S. Weld