Experiments with dimensionality reduction (physics-based, random projection, etc.)
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Updated
Jul 26, 2021
Experiments with dimensionality reduction (physics-based, random projection, etc.)
Applying many advanced unsupervised learning algorithms and techniques
Basic exploration of Higgs boson data
Sklearn, PCA, t-SNE, Isomap, NMF, Random Projection, Spectral Embedding
Efficient Bayesian high-dimensional classification via random projection with application to gene expression data
Random Projection for deep Neural Networks parameters number reduction.
Similarity Detection on Wikipedia Articles using MinHash and Random Projection implemented in Hadoop/Spark
Classical and Neural Dimensionality Reduction Techniques
This package is a Julia implementation of random projections.
Holds code for near-duplicate image parser using optimized image classifiers.
Implement of paper "Unsupervised Outlier Detection using Random Subspace and Subsampling Ensembles of Dirichlet Process Mixtures"
Summer@ICERM 2020 - Random Projections
Code demo to reproduce the experimental results of our NeurIPS 2022 paper "Approximate Euclidean lengths and distances beyond Johnson-Lindenstrauss"
A little lab of learning algorithms (in LUA). Less XAI, but better
A comparison between some dimension reduction algorithms
[CVPR 2023] Adversarial Robustness via Random Projection Filters
SHARP: Single-cell RNA-seq Hyper-fast and Accurate processing via ensemble Random Projection
Recognize one of six human activities such as standing, sitting, and walking using a Softmax Classifier trained on mobile phone sensor data.
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