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Found 5 papers, 2 papers with code
Sample Space Truncation on Boltzmann Machines
We present a lightweight variant of Boltzmann machines via sample space truncation, called a truncated Boltzmann machine (TBM), which has not been investigated before while can be naturally introduced from the log-linear model viewpoint.
Transductive Boltzmann Machines
We present transductive Boltzmann machines (TBMs), which firstly achieve transductive learning of the Gibbs distribution.
Legendre Decomposition for Tensors
We present a novel nonnegative tensor decomposition method, called Legendre decomposition, which factorizes an input tensor into a multiplicative combination of parameters.
Bias-Variance Decomposition for Boltzmann Machines
We achieve bias-variance decomposition for Boltzmann machines using an information geometric formulation.
Tensor Balancing on Statistical Manifold
To theoretically prove the correctness of the algorithm, we model tensors as probability distributions in a statistical manifold and realize tensor balancing as projection onto a submanifold.
