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» Machine-Learning Applications of Algorithmic Randomness
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ICML
2000
IEEE
14 years 9 days ago
Using Knowledge to Speed Learning: A Comparison of Knowledge-based Cascade-correlation and Multi-task Learning
Cognitive modeling with neural networks unrealistically ignores the role of knowledge in learning by starting from random weights. It is likely that effective use of knowledge by ...
Thomas R. Shultz, François Rivest
ICML
2004
IEEE
14 years 8 months ago
Sequential skewing: an improved skewing algorithm
This paper extends previous work on the Skewing algorithm, a promising approach that allows greedy decision tree induction algorithms to handle problematic functions such as parit...
Soumya Ray, David Page
ICML
2004
IEEE
14 years 1 months ago
Kernel-based discriminative learning algorithms for labeling sequences, trees, and graphs
We introduce a new perceptron-based discriminative learning algorithm for labeling structured data such as sequences, trees, and graphs. Since it is fully kernelized and uses poin...
Hisashi Kashima, Yuta Tsuboi
ML
2000
ACM
105views Machine Learning» more  ML 2000»
13 years 7 months ago
Multiple Comparisons in Induction Algorithms
Abstract. A single mechanism is responsible for three pathologies of induction algorithms: attribute selection errors, overfitting, and oversearching. In each pathology, induction ...
David D. Jensen, Paul R. Cohen
ICML
2006
IEEE
14 years 8 months ago
An empirical comparison of supervised learning algorithms
A number of supervised learning methods have been introduced in the last decade. Unfortunately, the last comprehensive empirical evaluation of supervised learning was the Statlog ...
Rich Caruana, Alexandru Niculescu-Mizil