ArticleEntropy (Basel, Switzerland)2020
Fractional Norms and Quasinorms Do Not Help to Overcome the Curse of Dimensionality.
Article in Entropy (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
8 citing papers in PubMed.
- Robust estimation of the intrinsic dimension of data sets with quantum cognition machine learning.Scientific reports · 2025Article
- Ordinal Classification with Distance Regularization for Robust Brain Age Prediction.IEEE Winter Conference on Applications of Computer Vision. IEEE Winter Conference on Applications of Computer Vision · 2024Article
- Domain Adaptation Principal Component Analysis: Base Linear Method for Learning with Out-of-Distribution Data.Entropy (Basel, Switzerland) · 2022Article
- A Fast kNN Algorithm Using Multiple Space-Filling Curves.Entropy (Basel, Switzerland) · 2022Article
- A Novel Framework for the Identification of Reference DNA Methylation Libraries for Reference-Based Deconvolution of Cellular Mixtures.Frontiers in bioinformatics · 2022Article
- Towards ML-Based Diagnostics of Laser-Plasma Interactions.Sensors (Basel, Switzerland) · 2021Article
- Scikit-Dimension: A Python Package for Intrinsic Dimension Estimation.Entropy (Basel, Switzerland) · 2021Article
- High-Dimensional Separability for One- and Few-Shot Learning.Entropy (Basel, Switzerland) · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
The curse of dimensionality causes the well-known and widely discussed problems for machine learning methods. There is a hypothesis that using the Manhattan distance and even fractional lp quasinorms (for
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.