Co-occurring keywords · papers mentioning both
Papers
Demixed shared component analysis of neural population data from multiple brain areas
NeurIPS 2020
Efficient Online Learning of Optimal Rankings: Dimensionality Reduction via Gradient Descent
NeurIPS 2020
Eliminating the Invariance on the Loss Landscape of Linear Autoencoders
ICML 2020
Explicitly Encouraging Low Fractional Dimensional Trajectories Via Reinforcement Learning
CoRL 2020
Federated Principal Component Analysis
NeurIPS 2020
Flows for simultaneous manifold learning and density estimation
NeurIPS 2020
Gain with no Pain: Efficiency of Kernel-PCA by Nyström Sampling
AISTATS 2020
Gaussian Sketching yields a J-L Lemma in RKHS
AISTATS 2020
Going Beyond T-SNE: Exposing whatlies in Text Embeddings
EMNLP 2020
GP-VAE: Deep Probabilistic Time Series Imputation
AISTATS 2020
Graph-Based Decoding Model for Functional Alignment of Unaligned fMRI Data
AAAI 2020
Improved Subsampled Randomized Hadamard Transform for Linear SVM
AAAI 2020
Improving Neural Network Training in Low Dimensional Random Bases
NeurIPS 2020
IMS at SemEval-2020 Task 1: How Low Can You Go? Dimensionality in Lexical Semantic Change Detection
SemEval 2020
Input-Sparsity Low Rank Approximation in Schatten Norm
ICML 2020
IVFS: Simple and Efficient Feature Selection for High Dimensional Topology Preservation
AAAI 2020
Learning Polynomials in Few Relevant Dimensions
COLT 2020
Learning sparse codes from compressed representations with biologically plausible local wiring constraints
NeurIPS 2020
Manifold structure in graph embeddings
NeurIPS 2020
Multi-Mutual Consistency Induced Transfer Subspace Learning for Human Motion Segmentation
CVPR 2020
Neural Decomposition: Functional ANOVA with Variational Autoencoders
AISTATS 2020
Optimal Iterative Sketching Methods with the Subsampled Randomized Hadamard Transform
NeurIPS 2020
Perturbation Bounds for Procrustes, Classical Scaling, and Trilateration, with Applications to Manifold Learning
JMLR 2020
Precise expressions for random projections: Low-rank approximation and randomized Newton
NeurIPS 2020
Proximity Preserving Binary Code Using Signed Graph-Cut
AAAI 2020