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Dimensionality Reduction

707 papers

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Papers

Solving Large-Scale Sparse PCA to Certifiable (Near) Optimality JMLR 2022
Supervised Dimensionality Reduction and Visualization using Centroid-Encoder JMLR 2022
Projected Statistical Methods for Distributional Data on the Real Line with the Wasserstein Metric JMLR 2022
Attraction-Repulsion Spectrum in Neighbor Embeddings JMLR 2022
Sufficient reductions in regression with mixed predictors JMLR 2022
Power Iteration for Tensor PCA JMLR 2022
Manifold Coordinates with Physical Meaning JMLR 2022
Low-rank Tensor Learning with Nonconvex Overlapped Nuclear Norm Regularization JMLR 2022
A Forward Approach for Sufficient Dimension Reduction in Binary Classification JMLR 2022
Projected Robust PCA with Application to Smooth Image Recovery JMLR 2022
A Computationally Efficient Framework for Vector Representation of Persistence Diagrams JMLR 2022
Theoretical Foundations of t-SNE for Visualizing High-Dimensional Clustered Data JMLR 2022
Kernel Autocovariance Operators of Stationary Processes: Estimation and Convergence JMLR 2022
Statistical Optimality and Computational Efficiency of Nystrom Kernel PCA JMLR 2022
Vector-Valued Least-Squares Regression under Output Regularity Assumptions JMLR 2022
Dynamic Programming in Rank Space: Scaling Structured Inference with Low-Rank HMMs and PCFGs NAACL 2022
Consistent Estimation for PCA and Sparse Regression with Oblivious Outliers NIPS 2021
PANTHER: Pathway Augmented Nonnegative Tensor Factorization for HighER-order Feature Learning AAAI 2021
Low-Rank Registration Based Manifolds for Convection-Dominated PDEs AAAI 2021
Bringing UMAP Closer to the Speed of Light with GPU Acceleration AAAI 2021
Fast and Compact Bilinear Pooling by Shifted Random Maclaurin AAAI 2021
Binary Matrix Factorisation via Column Generation AAAI 2021
Clustering Ensemble Meets Low-rank Tensor Approximation AAAI 2021
Self-Paced Two-dimensional PCA AAAI 2021
Fast PCA in 1-D Wasserstein Spaces via B-splines Representation and Metric Projection AAAI 2021