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TNN
1998
111views more  TNN 1998»
14 years 9 months ago
Asymptotic distributions associated to Oja's learning equation for neural networks
— In this paper, we perform a complete asymptotic performance analysis of the stochastic approximation algorithm (denoted subspace network learning algorithm) derived from Oja’...
Jean Pierre Delmas, Jean-Francois Cardos
AAAI
2004
14 years 11 months ago
Distributed Representation of Syntactic Structure by Tensor Product Representation and Non-Linear Compression
Representing lexicons and sentences with the subsymbolic approach (using techniques such as Self Organizing Map (SOM) or Artificial Neural Network (ANN)) is a relatively new but i...
Heidi H. T. Yeung, Peter W. M. Tsang
UAI
2003
14 years 11 months ago
Large-Sample Learning of Bayesian Networks is NP-Hard
In this paper, we provide new complexity results for algorithms that learn discrete-variable Bayesian networks from data. Our results apply whenever the learning algorithm uses a ...
David Maxwell Chickering, Christopher Meek, David ...
FOCI
2007
IEEE
15 years 3 months ago
Almost All Learning Machines are Singular
— A learning machine is called singular if its Fisher information matrix is singular. Almost all learning machines used in information processing are singular, for example, layer...
Sumio Watanabe
CVPR
2012
IEEE
13 years 13 hour ago
Sum-product networks for modeling activities with stochastic structure
This paper addresses recognition of human activities with stochastic structure, characterized by variable spacetime arrangements of primitive actions, and conducted by a variable ...
Mohamed R. Amer, Sinisa Todorovic