mlsanityData to 7 Oct 2026

Principal Component Classification

arXiv 2210.12746 ↗First posted 23 Oct 2022cs.LG cs.CV stat.MLcited by 0

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Abstract (arXiv)

We propose to directly compute classification estimates by learning features encoded with their class scores using PCA. Our resulting model has a encoder-decoder structure suitable for supervised learning, it is computationally efficient and performs well for classification on several datasets.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 5 of its 16 references that are in the map. First posted on arXiv 23 Oct 2022.

Builds on

5 of 16 references.

References · 5

  1. 2018An Intriguing Failing of Convolutional Neural Networks and the CoordConv Solutioncited by 302
  2. 2021Efficient-CapsNet: Capsule Network with Self-Attention Routingcited by 41
  3. 2020EigenGame: PCA as a Nash Equilibriumcited by 39
  4. 2016Geometric Mean Metric Learningcited by 22
  5. 2022Robust Geometric Metric Learningcited by 3

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