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Computer Science > Machine Learning

arXiv:2303.11958 (cs)
[Submitted on 19 Mar 2023]

Title:Formulation of Weighted Average Smoothing as a Projection of the Origin onto a Convex Polytope

Authors:Kaan Gokcesu, Hakan Gokcesu
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Abstract:Our study focuses on determining the best weight windows for a weighted moving average smoother under squared loss. We show that there exists an optimal weight window that is symmetrical around its center. We study the class of tapered weight windows, which decrease in weight as they move away from the center. We formulate the corresponding least squares problem as a quadratic program and finally as a projection of the origin onto a convex polytope. Additionally, we provide some analytical solutions to the best window when some conditions are met on the input data.
Comments: arXiv admin note: substantial text overlap with arXiv:2203.02997
Subjects: Machine Learning (cs.LG); Signal Processing (eess.SP); Optimization and Control (math.OC); Machine Learning (stat.ML)
Cite as: arXiv:2303.11958 [cs.LG]
  (or arXiv:2303.11958v1 [cs.LG] for this version)
  https://doi.org/10.48550/arXiv.2303.11958

Submission history

From: Kaan Gokcesu [view email]
[v1] Sun, 19 Mar 2023 22:40:39 UTC (13 KB)
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