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Dimensionality Reduction

707 papers

Papers per year

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Papers

Grassmannian Manifold Optimization Assisted Sparse Spectral Clustering CVPR 2017
Robust Joint and Individual Variance Explained CVPR 2017
Explaining and Generalizing Skip-Gram through Exponential Family Principal Component Analysis EACL 2017
Word Embeddings based on Fixed-Size Ordinally Forgetting Encoding EMNLP 2017
Word Re-Embedding via Manifold Dimensionality Retention EMNLP 2017
Communication-efficient Algorithms for Distributed Stochastic Principal Component Analysis ICML 2017
Tensor Decomposition with Smoothness ICML 2017
Partitioned Tensor Factorizations for Learning Mixed Membership Models ICML 2017
Tensor Decomposition via Simultaneous Power Iteration ICML 2017
Storage Fit Learning with Unlabeled Data IJCAI 2017
Fast Recursive Low-rank Tensor Learning for Regression IJCAI 2017
Projective Low-rank Subspace Clustering via Learning Deep Encoder IJCAI 2017
Reconstruction-based Unsupervised Feature Selection: An Embedded Approach IJCAI 2017
Flexible Orthogonal Neighborhood Preserving Embedding IJCAI 2017
Two dimensional Large Margin Nearest Neighbor for Matrix Classification IJCAI 2017
Angle Principal Component Analysis IJCAI 2017
Adaptive Hypergraph Learning for Unsupervised Feature Selection IJCAI 2017
Functional Principal Component Analysis of Vocal Tract Area Functions INTERSPEECH 2017
Recovering PCA and Sparse PCA via Hybrid-(l1,l2) Sparse Sampling of Data Elements JMLR 2017
Quantifying the Informativeness of Similarity Measurements JMLR 2017
Robust Discriminative Clustering with Sparse Regularizers JMLR 2017
Kernel Partial Least Squares for Stationary Data JMLR 2017
Dimension Estimation Using Random Connection Models JMLR 2017
Adaptive Randomized Dimension Reduction on Massive Data JMLR 2017
Single Pass PCA of Matrix Products NIPS 2016