Dimensionality Reduction
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Benchmarks
Most implemented
UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction
Adversarial Autoencoders
XGBoost: A Scalable Tree Boosting System
ECA-Net: Efficient Channel Attention for Deep Convolutional Neural Networks
Rethinking Spatial Dimensions of Vision Transformers
Towards K-means-friendly Spaces: Simultaneous Deep Learning and Clustering
Papers
Dimensionality Reduction for Hyperspectral Image Classification
This paper addresses the issue of supervised classification in the context of hyperspectral satellite images. It deals with two fundamental aspects: dimensionality reduction of data and the selection of appropriate super…
Hyperspectral Image ClassificationDimensionality ReductionHybrid Quantum-Classical NLP Classification with Compact Semantic Representations: An Experimental Analysis of Representation Compression
Large language and sentence-embedding models provide rich semantic representations, but their high dimensionality poses a challenge for near-term quantum machine learning (QML), where quantum circuits can process only a …
Quantum Machine LearningDimensionality ReductionEfficient Estimation of High Information Projections using Nearest Neighbours
An intuitive method for dimensionality reduction is proposed, which is highly effective for finding interesting projections of multivariate data. Following similar intuitive motivation to a number of existing techniques,…
Dimensionality ReductionOutlier DetectionAristotelian Manifolds: Leveraging Platonic Perceptual Features for Backpropagation Free Rapid Concept Learning
This paper formalizes and systematically characterizes Aristotelian Manifolds, a generalized structural framework built upon the Platonic Representation Hypothesis. We position high-capacity foundation models as universa…
Dimensionality ReductionHAF: Adapting Generalist VLAs to Humanoid Whole-Body Loco-manipulation via Hierarchical Action Flow and Spectral Latent RL
Humanoid robots hold great promise as general-purpose agents in human-centered environments, yet generalist vision-language-action (VLA) foundation models are not readily applicable to humanoid whole-body loco-manipulati…
Dimensionality ReductionReinforcement LearningA Multispectral Framework for the Detection of Calcium Carbide-Induced Ripening and Shelf-Life Estimation in Climacteric Fruits
Significant health risks are associated with the illegal, yet commonly practiced use of industrial-grade Calcium Carbide (CaC2) for ripening climacteric fruits like mango and banana, which leaves behind trace residues of…
Dimensionality ReductionFeature Engineering