dimensionality reduction

Near Optimal Sketching of Low-Rank Tensor Regression NeurIPS 2017 Practical Hash Functions for Similarity Estimation and Dimensionality Reduction NeurIPS 2017 Principal Variety Analysis CoRL 2017 Projective Low-rank Subspace Clustering via Learning Deep Encoder IJCAI 2017 Quantifying the Informativeness of Similarity Measurements JMLR 2017 Reconstruction-based Unsupervised Feature Selection: An Embedded Approach IJCAI 2017 Robust Discriminative Clustering with Sparse Regularizers JMLR 2017 Robust Joint and Individual Variance Explained CVPR 2017 See without looking: joint visualization of sensitive multi-site datasets IJCAI 2017 Semi-supervised Orthogonal Graph Embedding with Recursive Projections IJCAI 2017 Sifting Common Information from Many Variables IJCAI 2017 Simple strategies for recovering inner products from coarsely quantized random projections NeurIPS 2017 Single-Pass PCA of Large High-Dimensional Data IJCAI 2017 Skip-Gram − Zipf + Uniform = Vector Additivity ACL 2017 Sparse Embedded k-Means Clustering NeurIPS 2017 Spectral Clustering Based on Local PCA JMLR 2017 Structured adaptive and random spinners for fast machine learning computations AISTATS 2017 The Unreasonable Effectiveness of Structured Random Orthogonal Embeddings NeurIPS 2017 Towards K-means-friendly Spaces: Simultaneous Deep Learning and Clustering ICML 2017 Word Embeddings based on Fixed-Size Ordinally Forgetting Encoding EMNLP 2017 Word Re-Embedding via Manifold Dimensionality Retention EMNLP 2017 Additive Approximations in High Dimensional Nonparametric Regression via the SALSA ICML 2016 Compact Bilinear Pooling CVPR 2016 Correlated-PCA: Principal Components' Analysis when Data and Noise are Correlated NeurIPS 2016 Dimensionality Reduction of Massive Sparse Datasets Using Coresets NeurIPS 2016