On the minimax risk of dictionary learning
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... WebMinimax reconstruction risk of convolutional sparse dictionary learning. AISTATS, 2024. Yang Y, Gu Q, Zhang Y, Sasaki T, Crivello J, O'Neill R, Gilbert DM, and Ma J. Continuous-trait probabilistic model for comparing multi-species functional genomic data. Cell Systems, 7(2):208-218.e11 ...
On the minimax risk of dictionary learning
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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 … WebRelevant books, articles, theses on the topic 'Estimation de la norme minimale.' Scholarly sources with full text pdf download. Related research topic ideas.
Web[28] derived the risk bound for minimax learning by exploiting the dual representation of worst-case risk. However, their minimax risk bound would go to infinity and thus … Web17 de mai. de 2016 · In this regard, the paper provides a general lower bound on the minimax risk and also adapts the proof techniques for equivalent results using sparse and Gaussian coefficient models. The reported results suggest that the sample complexity of dictionary learning for tensor data can be significantly lower than that for unstructured …
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 … 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,
Web30 de jan. de 2024 · Minimax Lower Bounds on Dictionary Learning for Tensor Data Abstract: This paper provides fundamental limits on the sample complexity of estimating …
granite countertop protector matsWebThis paper provides fundamental limits on the sample complexity of estimating dictionaries for tensor data. ... Minimax Lower Bounds on Dictionary Learning for Tensor Data ... granite countertop providers in portlandWebOn 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 … chin lee cny 2023 menuWeb3 de abr. de 2024 · The NEUSS model first derives the asset embeddings for each asset (ETF) based on its financial news and machine learning methods such as UMAP, paragraph models and word embeddings. Then we obtain a collection of the basis assets based on their asset embeddings. After that, for each stock, we select the basis assets to … granite countertop protectionWeb: (7) A. Minimax risk analysis We are interested in lower bounding the minimax risk for estimating D based on observations Y, which is defined as the worst-case mean squared error (MSE) that can be obtained by the best KS dictionary estimator Db(Y). That is, " = inf Db sup 2X(0;r) E Y n Db(Y) D 2 F granite countertop protectorWeb12 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 … chinle district court chinle azWebMinimax lower bounds for Kronecker-structured dictionary learning. Authors: Zahra Shakeri. Dept. of Electrical and Computer Engineering, Rutgers University, Piscataway, New Jersey 08854, United States ... chin lee grocery