Dimensionality Reduction

Dimensionality reduction: theoretical perspective on practical measures NeurIPS 2019 Dimension-Free Error Bounds from Random Projections AAAI 2019 Double Nuclear Norm Based Low Rank Representation on Grassmann Manifolds for Clustering CVPR 2019 Fast and Robust Shortest Paths on Manifolds Learned from Data AISTATS 2019 Geometry-Aware Maximum Likelihood Estimation of Intrinsic Dimension ACML 2019 Heuristic Search Algorithm for Dimensionality Reduction Optimally Combining Feature Selection and Feature Extraction AAAI 2019 Hyperbolic Ordinal Embedding ACML 2019 Improving Word Embeddings Using Kernel PCA ACL 2019 K-Nearest Neighbors Hashing CVPR 2019 Latent distance estimation for random geometric graphs NeurIPS 2019 Learning-Based Low-Rank Approximations NeurIPS 2019 Learning nonlinear level sets for dimensionality reduction in function approximation NeurIPS 2019 Local Regularization of Noisy Point Clouds: Improved Global Geometric Estimates and Data Analysis JMLR 2019 Low Permutation-rank Matrices: Structural Properties and Noisy Completion JMLR 2019 Low-Rank Tensor Completion With a New Tensor Nuclear Norm Induced by Invertible Linear Transforms CVPR 2019 Manifold denoising by Nonlinear Robust Principal Component Analysis NeurIPS 2019 Manifold Distance-Based Over-Sampling Technique for Class Imbalance Learning AAAI 2019 MFPCA: Multiscale Functional Principal Component Analysis AAAI 2019 Multi-Criteria Dimensionality Reduction with Applications to Fairness NeurIPS 2019 Multi-Frequency Vector Diffusion Maps ICML 2019 Multilingual Detection of Hate Speech Against Immigrants and Women in Twitter at SemEval-2019 Task 5: Frequency Analysis Interpolation for Hate in Speech Detection SemEval 2019 No Pressure! Addressing the Problem of Local Minima in Manifold Learning Algorithms NeurIPS 2019 On Geometric Alignment in Low Doubling Dimension AAAI 2019 Online Factorization and Partition of Complex Networks by Random Walk UAI 2019 On Robustness of Principal Component Regression NeurIPS 2019