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Dimensionality Reduction

707 papers

Papers per year

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Papers

Neighborhood Structure Assisted Non-negative Matrix Factorization and Its Application in Unsupervised Point-wise Anomaly Detection JMLR 2021
Optimal Structured Principal Subspace Estimation: Metric Entropy and Minimax Rates JMLR 2021
Subspace Clustering through Sub-Clusters JMLR 2021
Geometric structure of graph Laplacian embeddings JMLR 2021
Communication-Efficient Distributed Covariance Sketch, with Application to Distributed PCA JMLR 2021
Guided Visual Exploration of Relations in Data Sets JMLR 2021
Inference for Multiple Heterogeneous Networks with a Common Invariant Subspace JMLR 2021
A Sharp Blockwise Tensor Perturbation Bound for Orthogonal Iteration JMLR 2021
Integrated Principal Components Analysis JMLR 2021
Regularized spectral methods for clustering signed networks JMLR 2021
LDLE: Low Distortion Local Eigenmaps JMLR 2021
Non-linear, Sparse Dimensionality Reduction via Path Lasso Penalized Autoencoders JMLR 2021
A Data Driven, Convex Optimization Approach to Learning Koopman Operators L4DC 2021
On Geodesic Distances and Contextual Embedding Compression for Text Classification NAACL 2021
Robust principal component analysis for generalized multi-view models UAI 2021
Demixed shared component analysis of neural population data from multiple brain areas NIPS 2020
Federated Principal Component Analysis NIPS 2020
Estimation and Imputation in Probabilistic Principal Component Analysis with Missing Not At Random Data NIPS 2020
Non-reversible Gaussian processes for identifying latent dynamical structure in neural data NIPS 2020
Manifold structure in graph embeddings NIPS 2020
Revisiting the Sample Complexity of Sparse Spectrum Approximation of Gaussian Processes NIPS 2020
Node Embeddings and Exact Low-Rank Representations of Complex Networks NIPS 2020
Steering Distortions to Preserve Classes and Neighbors in Supervised Dimensionality Reduction NIPS 2020
Learning Feature Sparse Principal Subspace NIPS 2020
Latent Dynamic Factor Analysis of High-Dimensional Neural Recordings NIPS 2020