27 search results - page 1 / 6 » Learning Stochastic Perceptrons Under k-Blocking Distributio... |
NIPS
1994
15 years 27 days ago
1994
We present a statistical method that PAC learns the class of stochastic perceptrons with arbitrary monotonic activation function and weights wi {-1, 0, +1} when the probability d...
COLT
1999
Springer
15 years 3 months ago
1999
Springer
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...
ICML
2004
IEEE
16 years 12 days ago
2004
IEEE
We propose to study links between three important classification algorithms: Perceptrons, Multi-Layer Perceptrons (MLPs) and Support Vector Machines (SVMs). We first study ways to...
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ML
2007
ACM
14 years 11 months ago
2007
ACM
We propose a general-purpose stochastic optimization algorithm, the so-called annealing stochastic approximation Monte Carlo (ASAMC) algorithm, for neural network training. ASAMC c...
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NN
2007
Springer
14 years 11 months ago
2007
Springer
Several scientists suggested that certain perceptual qualities are based on sensorimotor anticipation: for example, the softness of a sponge is perceived by anticipating the sensa...