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» Learning with the Set Covering Machine
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113
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IJCNN
2007
IEEE
15 years 9 months ago
Transfer Learning in Decision Trees
— Most research in machine learning focuses on scenarios in which a learner faces a single learning task, independently of other learning tasks or prior knowledge. In reality, ho...
Jun Won Lee, Christophe G. Giraud-Carrier
125
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COLT
1999
Springer
15 years 7 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
96
Voted
ICALT
2005
IEEE
15 years 8 months ago
Authoring Educational Topic Maps: Can We Make It Easier?
In this paper we examine some problems related to capturing the structure and the topic name space of learning content in the context of Topic Map authoring. We demonstrate that t...
Darina Dicheva, Christo Dichev
119
Voted
AAAI
2000
15 years 4 months ago
A Quantitative Study of Small Disjuncts
Systems that learn from examples often express the learned concept in the form of a disjunctive description. Disjuncts that correctly classify few training examples are known as s...
Gary M. Weiss, Haym Hirsh
119
Voted
ICML
2009
IEEE
16 years 3 months ago
Proto-predictive representation of states with simple recurrent temporal-difference networks
We propose a new neural network architecture, called Simple Recurrent Temporal-Difference Networks (SR-TDNs), that learns to predict future observations in partially observable en...
Takaki Makino