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Akademický článek

LOCAL LINEAR EMBEDDING ALGORITHM FOR PARAMETER MATRIX MEASUREMENT IN SYMMETRIC POSITIVE DEFINITE MANIFOLD (MT)

Autor: LIU QingQiang, HE HongKai, ZHENG ChangMin, SUN YanRu, LIU ZiXuan

Publikováno v: Jixie qiangdu, Pp 1307-1314 (2022)

Most of the existing local linear embedding algorithms assume that the original data set is located in Euclidean space, but in reality almost all the original space is non-Euclidean space. Aiming at the problem that Euclidean space cannot effectively

Externí odkaz: https://doaj.org/article/62976ab839684fffb5b804003a020450

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Learning Pattern-Specific Experts for Time Series Forecasting Under Patch-level Distribution Shift

Autor: Sun, Yanru, Xie, Zongxia, Eldele, Emadeldeen, Chen, Dongyue, Hu, Qinghua, Wu, Min

Time series forecasting, which aims to predict future values based on historical data, has garnered significant attention due to its broad range of applications. However, real-world time series often exhibit complex non-uniform distribution with vary

Externí odkaz: http://arxiv.org/abs/2410.09836

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Hierarchical Classification Auxiliary Network for Time Series Forecasting

Autor: Sun, Yanru, Xie, Zongxia, Chen, Dongyue, Eldele, Emadeldeen, Hu, Qinghua

Deep learning has significantly advanced time series forecasting through its powerful capacity to capture sequence relationships. However, training these models with the Mean Square Error (MSE) loss often results in over-smooth predictions, making it

Externí odkaz: http://arxiv.org/abs/2405.18975

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