Dimensionality Reduction

Streaming Principal Component Analysis in Noisy Setting ICML 2018 Adaptive Hypergraph Learning for Unsupervised Feature Selection IJCAI 2017 Adaptive Randomized Dimension Reduction on Massive Data JMLR 2017 Additive Component Analysis CVPR 2017 Angle Principal Component Analysis IJCAI 2017 Approximation Algorithms for ℓ_0-Low Rank Approximation NeurIPS 2017 Communication-efficient Algorithms for Distributed Stochastic Principal Component Analysis ICML 2017 Compact Matrix Factorization With Dependent Subspaces CVPR 2017 Cross-Spectral Factor Analysis NeurIPS 2017 Diffusion Approximations for Online Principal Component Estimation and Global Convergence NeurIPS 2017 Dimension Estimation Using Random Connection Models JMLR 2017 Explaining and Generalizing Skip-Gram through Exponential Family Principal Component Analysis EACL 2017 Extracting low-dimensional dynamics from multiple large-scale neural population recordings by learning to predict correlations NeurIPS 2017 Fast Recursive Low-rank Tensor Learning for Regression IJCAI 2017 Fitting Low-Rank Tensors in Constant Time NeurIPS 2017 Flexible Orthogonal Neighborhood Preserving Embedding IJCAI 2017 Functional Principal Component Analysis of Vocal Tract Area Functions Interspeech 2017 Grassmannian Manifold Optimization Assisted Sparse Spectral Clustering CVPR 2017 Improved Graph Laplacian via Geometric Self-Consistency NeurIPS 2017 Kernel Feature Selection via Conditional Covariance Minimization NeurIPS 2017 Kernel Partial Least Squares for Stationary Data JMLR 2017 Matrix Norm Estimation from a Few Entries NeurIPS 2017 Near Optimal Sketching of Low-Rank Tensor Regression NeurIPS 2017 Partitioned Tensor Factorizations for Learning Mixed Membership Models ICML 2017 Principal Variety Analysis CoRL 2017