We present an approach for dictionary learning of action attributes via information maximization. We unify the class distribution and appearance information into an objective func...
We study the two party problem of randomly selecting a string among all the strings of length n. We want the protocol to have the property that the output distribution has high en...
Harry Buhrman, Matthias Christandl, Michal Kouck&y...
The Relevance Vector Machine (RVM) is a sparse approximate Bayesian kernel method. It provides full predictive distributions for test cases. However, the predictive uncertainties ...
We generalize Shimizu et al's (2006) ICA-based approach for discovering linear non-Gaussian acyclic (LiNGAM) Structural Equation Models (SEMs) from causally sufficient, conti...
Gustavo Lacerda, Peter Spirtes, Joseph Ramsey, Pat...
An analytical approach is presented for determining the response of a neuron or of the activity in a network of connected neurons, represented by systems of nonlinear ordinary stoc...