We present a new connectionist planning method TML90 . By interaction with an unknown environment, a world model is progressively constructed using gradient descent. For deriving ...
The naive Bayes model makes the often unrealistic assumption that the feature variables are mutually independent given the class variable. We interpret a violation of this assumpt...
Nevin Lianwen Zhang, Thomas D. Nielsen, Finn Verne...
We derive an optimal learning rule in the sense of mutual information maximization for a spiking neuron model. Under the assumption of small fluctuations of the input, we find a s...
Developing better methods for segmenting continuous text into words is important for improving the processing of Asian languages, and may shed light on how humans learn to segment...
Sharon Goldwater, Thomas L. Griffiths, Mark Johnso...
This paper proposes a novel method for learning probability models of subcategorization preference of verbs. We consider the issues of case dependencies and noun class generalizat...