WebIn particular, we analyze the minimax risk of the dictionary learning problem which governs the mean squared error (MSE) performance of any learning scheme, regardless of its computational complexity. WebThis paper identifies minimax rates of CSDL in terms of reconstruction risk, providing both lower and upper bounds in a variety of settings. Our results make minimal assumptions, …
Sample complexity bounds for dictionary learning of tensor data
WebDictionary learning is the problem of estimating the collection of atomic elements that provide a sparse representation of measured/collected signals or data. This paper finds fundamental limits on the sample complexity of estimating dictionaries for tensor data by proving a lower bound on the minimax risk. Web15 de jul. de 2016 · The focus of this paper is on second-order tensor data, with the underlying dictionaries constructed by taking the Kronecker product of two smaller … cite young goodman brown
On the Minimax Risk of Dictionary Learning - IEEE Journals
Web20 de jul. de 2015 · On the Minimax Risk of Dictionary Learning arXiv Authors: Alexander Jung Aalto University Yonina Eldar Weizmann Institute of Science Norbert Görtz Abstract … WebIt is assumed the data are generated by linear combinations of these structured dictionary atoms and observed through white Gaussian noise. This work first provides a general lower bound on the minimax risk of dictionary learning for such tensor data and then adapts the proof techniques for specialized results in the case of sparse and sparse-Gaussian … WebWe consider the problem of dictionary learning under the assumption that the observed signals can be represented as sparse linear combinations of the columns of a single … cite yourself apa 7