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dimensionality reduction

720 papers

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Also known as

DR

Co-occurring keywords

manifold learning (402) principal component analysis (316) feature extraction (1578) random projection (145) unsupervised learning (3255) representation learning (6174) kernel methods (1096) metric learning (1189) feature selection (649) matrix factorization (529)

Papers

The Fast Johnson-Lindenstrauss Transform Is Even Faster ICML 2023
An Online and Unified Algorithm for Projection Matrix Vector Multiplication with Application to Empirical Risk Minimization AISTATS 2023
Isometric Manifold Learning Using Hierarchical Flow AAAI 2023
Kernelized Diffusion Maps COLT 2023
Bottleneck Structure in Learned Features: Low-Dimension vs Regularity Tradeoff NIPS 2023
SOM-CPC: Unsupervised Contrastive Learning with Self-Organizing Maps for Structured Representations of High-Rate Time Series ICML 2023
On the Power of SVD in the Stochastic Block Model NIPS 2023
WizMap: Scalable Interactive Visualization for Exploring Large Machine Learning Embeddings ACL 2023
BASiS: Batch Aligned Spectral Embedding Space CVPR 2023
Uncovering motifs of concurrent signaling across multiple neuronal populations NIPS 2023
Fair Neighbor Embedding ICML 2023
Density estimation on low-dimensional manifolds: an inflation-deflation approach JMLR 2023
Contrastive Learning with the Feature Reconstruction Amplifier AAAI 2023
On Slicing Optimality for Mutual Information NIPS 2023
Dimensionality-Varying Diffusion Process CVPR 2023
MMGP: a Mesh Morphing Gaussian Process-based machine learning method for regression of physical problems under nonparametrized geometrical variability NIPS 2023
A Novel Stochastic Gradient Descent Algorithm for Learning Principal Subspaces AISTATS 2023
Matrix Compression via Randomized Low Rank and Low Precision Factorization NIPS 2023
White-Box Transformers via Sparse Rate Reduction NIPS 2023
Featured Graph Coarsening with Similarity Guarantees ICML 2023
Computing Approximate $\ell_p$ Sensitivities NIPS 2023
Dimensionality Reduction and Wasserstein Stability for Kernel Regression JMLR 2023
ActUp: Analyzing and Consolidating tSNE and UMAP IJCAI 2023
Extending Kernel PCA through Dualization: Sparsity, Robustness and Fast Algorithms ICML 2023
Neural Implicit Flow: a mesh-agnostic dimensionality reduction paradigm of spatio-temporal data JMLR 2023