principal component analysis

Bayesian Eigenobjects: A Unified Framework for 3D Robot Perception RSS 2017 Communication-efficient Algorithms for Distributed Stochastic Principal Component Analysis ICML 2017 Computationally Efficient Robust Sparse Estimation in High Dimensions COLT 2017 Designing Illuminant Spectral Power Distributions for Surface Classification CVPR 2017 Diffusion Approximations for Online Principal Component Estimation and Global Convergence NeurIPS 2017 Explaining and Generalizing Skip-Gram through Exponential Family Principal Component Analysis EACL 2017 Exploiting Eigenposteriors for Semi-Supervised Training of DNN Acoustic Models with Sequence Discrimination Interspeech 2017 Fast Rates for Empirical Risk Minimization of Strict Saddle Problems COLT 2017 How Close Are the Eigenvectors of the Sample and Actual Covariance Matrices? ICML 2017 Intrinsic Grassmann Averages for Online Linear and Robust Subspace Learning CVPR 2017 Learning the Multilinear Structure of Visual Data CVPR 2017 Minimax Gaussian Classification & Clustering AISTATS 2017 Outlier-Robust Tensor PCA CVPR 2017 Single-Pass PCA of Large High-Dimensional Data IJCAI 2017 Speaker Adaptation in DNN-Based Speech Synthesis Using d-Vectors Interspeech 2017 Spectral Clustering Based on Local PCA JMLR 2017 Thresholding Based Outlier Robust PCA COLT 2017 Uncorrelation and Evenness: a New Diversity-Promoting Regularizer ICML 2017 A General Framework for Consistency of Principal Component Analysis JMLR 2016 An Improved 3D Geometric Tongue Model Interspeech 2016 An Improved Gap-Dependency Analysis of the Noisy Power Method COLT 2016 A Pseudo-Bayesian Algorithm for Robust PCA NeurIPS 2016 Convergence of Stochastic Gradient Descent for PCA ICML 2016 Dimensionality Reduction of Massive Sparse Datasets Using Coresets NeurIPS 2016 Exploiting Hidden-Layer Responses of Deep Neural Networks for Language Recognition Interspeech 2016