dimensionality reduction

720 papers

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Also known as

SDR PCA 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

On Differentially Private Subspace Estimation in a Distribution-Free Setting NIPS 2024

Learned Transformer Position Embeddings Have a Low-Dimensional Structure ACL 2024

The Effective Number of Shared Dimensions Between Paired Datasets AISTATS 2024

AnnoPlot: Interactive Visualizations of Text Annotations EACL 2024

Navigating the Effect of Parametrization for Dimensionality Reduction NIPS 2024

The tree autoencoder model, with application to hierarchical data visualization NIPS 2024

Selective Deep Autoencoder for Unsupervised Feature Selection AAAI 2024

Matryoshka-Adaptor: Unsupervised and Supervised Tuning for Smaller Embedding Dimensions EMNLP 2024

ESPACE: Dimensionality Reduction of Activations for Model Compression NIPS 2024

Approximating mutual information of high-dimensional variables using learned representations NIPS 2024

Are Neurons Actually Collapsed? On the Fine-Grained Structure in Neural Representations ICML 2023

Dimensionality Reduction and Wasserstein Stability for Kernel Regression JMLR 2023

ActUp: Analyzing and Consolidating tSNE and UMAP IJCAI 2023

SOM-CPC: Unsupervised Contrastive Learning with Self-Organizing Maps for Structured Representations of High-Rate Time Series ICML 2023

Featured Graph Coarsening with Similarity Guarantees ICML 2023

A Unified Framework for Optimization-Based Graph Coarsening JMLR 2023

Extending Kernel PCA through Dualization: Sparsity, Robustness and Fast Algorithms ICML 2023

Contrastive Learning with the Feature Reconstruction Amplifier AAAI 2023

On Coresets for Clustering in Small Dimensional Euclidean spaces ICML 2023

White-Box Transformers via Sparse Rate Reduction NIPS 2023

The Fast Johnson-Lindenstrauss Transform Is Even Faster ICML 2023

MMGP: a Mesh Morphing Gaussian Process-based machine learning method for regression of physical problems under nonparametrized geometrical variability NIPS 2023

Geometric Autoencoders - What You See is What You Decode ICML 2023

Dimensionality Collapse: Optimal Measurement Selection for Low-Error Infinite-Horizon Forecasting AISTATS 2023

Dimensionality Reduction for General KDE Mode Finding ICML 2023