We prove that some multivariate linear tensor product problems are tractable in the worst case setting if they are defined as tensor products of univariate problems with logarithm...
We study the problem of learning an optimal Bayesian network in a constrained search space; skeletons are compelled to be subgraphs of a given undirected graph called the super-st...
Kaname Kojima, Eric Perrier, Seiya Imoto, Satoru M...
The problem of characterizing learnability is the most basic question of statistical learning theory. A fundamental and long-standing answer, at least for the case of supervised c...
We present an algorithm to infer causal relations between a set of measured variables on the basis of experiments on these variables. The algorithm assumes that the causal relatio...
Frederick Eberhardt, Patrik O. Hoyer, Richard Sche...
In this paper, the training sequence design for multiple-input multiple-output (MIMO) orthogonal frequencydivision multiplexing (OFDM) systems under the minimum mean square error (...
Hoang Duong Tuan, Ha Hoang Kha, Ha H. Nguyen, Viet...