mlsanityData to 7 Oct 2026

Smoothing with the Best Rectangle Window is Optimal for All Tapered Rectangle Windows

arXiv 2203.02997 ↗First posted 6 Mar 2022stat.ML cs.LG eess.SPcited by 3

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Abstract (arXiv)

We investigate the optimal selection of weight windows for the problem of weighted least squares. We show that weight windows should be symmetric around its center, which is also its peak. We consider the class of tapered rectangle window weights, which are nonincreasing away from the center. We show that the best rectangle window is optimal for such window definitions. We also extend our results to the least absolutes and more general case of arbitrary loss functions to find similar results.

Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 8 of its 60 references that are in the map. First posted on arXiv 6 Mar 2022.

Builds on

8 of 60 references.

References · 8

  1. 2018Flow Smoothing and Denoising: Graph Signal Processing in the Edge-Spacecited by 37
  2. 2021Generalized Huber Loss for Robust Learning and its Efficient Minimization for a Robust Statisticscited by 32
  3. 2018Sequential Outlier Detection based on Incremental Decision Treescited by 21
  4. 2021Optimally Efficient Sequential Calibration of Binary Classifiers to Minimize Classification Errorcited by 17
  5. 2020Recursive Experts: An Efficient Optimal Mixture of Learning Systems in Dynamic Environmentscited by 15
  6. 2021Nonparametric Extrema Analysis in Time Series for Envelope Extraction, Peak Detection and Clusteringcited by 12
  7. 2021Optimal and Efficient Algorithms for General Mixable Losses against Switching Oraclescited by 10
  8. 2022Nonconvex Extension of Generalized Huber Loss for Robust Learning and Pseudo-Mode Statisticscited by 8

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Cited by year

Citing papers per year: 2022: 3.

3 papers.

  1. 2022Blind Source Separation for Mixture of Sinusoids with Near-Linear Computational Complexitycited by 1
  2. 2022Robust, Nonparametric, Efficient Decomposition of Spectral Peaks under Distortion and Interferencecited by 0
  3. 2022An Auto-Regressive Formulation for Smoothing and Moving Mean with Exponentially Tapered Windowscited by 0