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NIPS
2007
15 years 8 months ago
Transfer Learning using Kolmogorov Complexity: Basic Theory and Empirical Evaluations
In transfer learning we aim to solve new problems using fewer examples using information gained from solving related problems. Transfer learning has been successful in practice, a...
M. M. Mahmud, Sylvian R. Ray
NIPS
2007
15 years 8 months ago
Sparse Feature Learning for Deep Belief Networks
Unsupervised learning algorithms aim to discover the structure hidden in the data, and to learn representations that are more suitable as input to a supervised machine than the ra...
Marc'Aurelio Ranzato, Y-Lan Boureau, Yann LeCun
COLING
1996
15 years 8 months ago
Learning Dependencies between Case Frame Slots
We address the problem of automatically acquiring case frame patterns (selectional patterns) from large corpus data. In particular, we l)ropose a method of learning dependencies b...
Hang Li, Naoki Abe
IJCAI
1993
15 years 8 months ago
Learning Decision Lists over Tree Patterns and Its Application
This paper introduces a new concept, a decision tree (or list) over tree patterns, which is a natural extension of a decision tree (or decision list), for dealing with tree struct...
Satoshi Kobayashi, Koichi Hori, Setsuo Ohsuga
FOCM
2006
97views more  FOCM 2006»
15 years 7 months ago
Learning Rates of Least-Square Regularized Regression
This paper considers the regularized learning algorithm associated with the leastsquare loss and reproducing kernel Hilbert spaces. The target is the error analysis for the regres...
Qiang Wu, Yiming Ying, Ding-Xuan Zhou