On the minimax risk of dictionary learning

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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 … Web29 de ago. de 2024 · On the Minimax Risk of Dictionary Learning Article Full-text available Jul 2015 IEEE T INFORM THEORY Alexander Jung Yonina Eldar Norbert Goertz We consider the problem of learning a...

Minimax Lower Bounds for Kronecker-Structured Dictionary Learning

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. Web30 de jan. de 2024 · minimax risk of the KS dictionary learning problem for the. case of general coefﬁcient distributions. Theorem 1. Consider a KS dictionary learning problem with. highland wool jumper

On the Minimax Risk of Dictionary Learning Papers With Code

http://spars2024.lx.it.pt/index_files/papers/SPARS2024_Paper_10.pdf Web17 de fev. de 2014 · Prior theoretical studies of dictionary learning have either focused on existing algorithms for non-KS dictionaries [5,[16][17][18][19][20][21] or lower bounds on … WebKS dictionary. The risk decreases with larger Nand K; in particular, larger Kfor ﬁxed mpmeans more structure, which simpliﬁes the estimation problem. The results for … small mammals of texas

IEEE TRANSACTIONS ON INFORMATION THEORY, VOL. 62, NO. 3, …

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WebWe consider the problem of learning a dictionary matrix from a number of observed signals, which are assumed to be generated via a linear model with a comm On the … http://www.inspirelab.us/wp-content/uploads/2024/07/ShakeriSarwateEtAl.BookChInfoTh21-Preprint.pdf highland woods golf and country club facebookWebDictionary 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. This lower bound depends on the … highland wrestling club

"WebWe consider the problem of learning a dictionary matrix from a number of observed signals, which are assumed to be generated via a linear model with a common underlying … " - On the minimax risk of dictionary learning

On the minimax risk of dictionary learning

Minimax lower bounds for Kronecker-structured dictionary learning

WebMinmax (sometimes Minimax, MM or saddle point) is a decision rule used in artificial intelligence, decision theory, game theory, statistics, and philosophy for minimizing the possible loss for a worst case (maximum loss) scenario.When dealing with gains, it is referred to as "maximin" – to maximize the minimum gain. Originally formulated for …

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Web9 de ago. de 2016 · 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 … Web8 de fev. de 2024 · Jung, A., Eldar, Y. C., & Görtz, N. (2016). On the Minimax Risk of Dictionary Learning. IEEE Transactions on Information Theory, 62, 62

Web1 de mar. de 2024 · This paper provides fundamental limits on the sample complexity of estimating dictionaries for tensor data. The specific focus of this work is on $K$th-order tensor data and the case where the... WebRelevant books, articles, theses on the topic 'Estimation de la norme minimale.' Scholarly sources with full text pdf download. Related research topic ideas.

Webthe information theory literature; these include restating the dictionary learning problem as a channel coding problem and connecting the analysis of minimax risk in statistical estimation to Fano’s inequality. In addition to highlighting the effects of different parameters on the sample complexity of dictionary learning, WebOn the Minimax Risk of Dictionary Learning Alexander Jung, Yonina C. Eldar,Fellow, IEEE, and Norbert Görtz,Senior Member, IEEE Abstract—We consider the problem of …

Web1 de abr. de 2024 · 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 linear combinations.

WebTranslations in context of "contenute a" in Italian-English from Reverso Context: a quelle contenute highland woods rv resort flWeb17 de fev. de 2014 · By following an established information-theoretic method based on Fanos inequality, we derive a lower bound on the minimax risk for a given dictionary learning problem. This lower bound yields a characterization of the sample-complexity, i.e., a lower bound on the required number of observations such that consistent dictionary … highland wright line logisticWebWe consider the problem of learning a dictionary matrix from a number of observed signals, which are assumed to be generated via a linear model with a common underlying … highland woodworking supplyWeb15 de jul. de 2016 · Minimax lower bounds for Kronecker-structured dictionary learning Abstract: Dictionary learning is the problem of estimating the collection of atomic elements that provide a sparse representation of measured/collected signals or data. highland woods warrensville heightsWeb12 de jan. de 2016 · On the Minimax Risk of Dictionary Learning Abstract: We consider the problem of learning a dictionary matrix from a number of observed signals, which … small man big mouth cyberpunk levelWebMinimax lower bounds for Kronecker-structured dictionary learning. Authors: Zahra Shakeri. Dept. of Electrical and Computer Engineering, Rutgers University, Piscataway, New Jersey 08854, United States ... highland x raysWebWe consider the problem of learning a dictionary matrix from a number of observed signals, which are assumed to be generated via a linear model with a common... Skip to … highland yacht club toronto