Supervised dimensionality reduction

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Most implemented papers archive 2025-07-28

18 shown of 18 papers with code (57 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• Adapting Text Embeddings for Causal Inference
  29 May 2019 4 repositories listed
  To address this challenge, we develop causally sufficient embeddings, low-dimensional document representations that preserve sufficient information for causal identification and allow for efficient estimation of causal…
• Learning Active Subspaces and Discovering Important Features with Gaussian Radial Basis Functions Neural Networks
  11 Jul 2023 2 repositories listed
  Providing a model that achieves a strong predictive performance and is simultaneously interpretable by humans is one of the most difficult challenges in machine learning research due to the conflicting nature of these…
• Supervised Dimensionality Reduction for Big Data
  5 Sep 2017 2 repositories listed
  To solve key biomedical problems, experimentalists now routinely measure millions or billions of features (dimensions) per sample, with the hope that data science techniques will be able to build accurate data-driven…
• Supervised Quadratic Feature Analysis: Information Geometry Approach for Dimensionality Reduction
  31 Jan 2025 1 repository listed
  Here, we present Supervised Quadratic Feature Analysis (SQFA), a linear dimensionality reduction method that maximizes Fisher-Rao distances between class distributions, by exploiting the information geometry of the…
• On the Inherent Robustness of One-Stage Object Detection against Out-of-Distribution Data
  7 Nov 2024 1 repository listed
  Finally, we discuss on the competitiveness of all tested methods against state-of-the-art OoD approaches for object detection models over the recently published Unknown Object Detection benchmark.
• An Embedding is Worth a Thousand Noisy Labels
  26 Aug 2024 1 repository listed
  The performance of deep neural networks scales with dataset size and label quality, rendering the efficient mitigation of low-quality data annotations crucial for building robust and cost-effective systems.
• Curvature Augmented Manifold Embedding and Learning
  21 Mar 2024 1 repository listed
  A new dimensional reduction (DR) and data visualization method, Curvature-Augmented Manifold Embedding and Learning (CAMEL), is proposed.
• Gravitational Dimensionality Reduction Using Newtonian Gravity and Einstein's General Relativity
  30 Oct 2022 1 repository listed
  Due to the effectiveness of using machine learning in physics, it has been widely received increased attention in the literature.
• Affective Manifolds: Modeling Machine's Mind to Like, Dislike, Enjoy, Suffer, Worry, Fear, and Feel Like A Human
  29 Aug 2022 1 repository listed
  More affective manifolds in the machine's mind can make it more realistic and effective.
• Supervised Dimensionality Reduction and Image Classification Utilizing Convolutional Autoencoders
  25 Aug 2022 1 repository listed
  It turned out that this methodology can also be greatly beneficial in enforcing explainability of deep learning architectures.
• SLISEMAP: Supervised dimensionality reduction through local explanations
  12 Jan 2022 1 repository listed
  Existing methods for explaining black box learning models often focus on building local explanations of model behaviour for a particular data item.
• Scalable semi-supervised dimensionality reduction with GPU-accelerated EmbedSOM
  3 Jan 2022 1 repository listed
  Dimensionality reduction methods have found vast application as visualization tools in diverse areas of science.
• Computer-aided Interpretable Features for Leaf Image Classification
  15 Jun 2021 1 repository listed
  The main image processing steps of our algorithm involves: i) Convert original image to RGB (Red-Green-Blue) image, ii) Gray scaling, iii) Gaussian smoothing, iv) Binary thresholding, v) Remove stalk, vi) Closing holes,…
• Stochastic Mutual Information Gradient Estimation for Dimensionality Reduction Networks
  1 May 2021 1 repository listed
  We present a dimensionality reduction network (MMINet) training procedure based on the stochastic estimate of the mutual information gradient.
• Supervised dimensionality reduction by a Linear Discriminant Analysis on pre-trained CNN features
  22 Jun 2020 1 repository listed
  The method finds the new classes close to the corresponding standard classes we took the data form.
• Supervised Discriminative Sparse PCA with Adaptive Neighbors for Dimensionality Reduction
  9 Jan 2020 1 repository listed
  Approaches that preserve only the local data structure, such as locality preserving projections, are usually unsupervised (and hence cannot use label information) and uses a fixed similarity graph.
• SRP: Efficient class-aware embedding learning for large-scale data via supervised random projections
  7 Nov 2018 1 repository listed
  While stochastic approximation strategies have been explored for unsupervised dimensionality reduction to tackle this challenge, such approaches are not well-suited for accelerating computational speed for supervised…
• Dimensionality Reduction using Similarity-induced Embeddings
  18 Jun 2017 1 repository listed
  The vast majority of Dimensionality Reduction (DR) techniques rely on second-order statistics to define their optimization objective.