Dimensionality Reduction

Non-reversible Gaussian processes for identifying latent dynamical structure in neural data NeurIPS 2020 Non-Rigid Structure from Motion: Prior-Free Factorization Method Revisited WACV 2020 ODE-Inspired Analysis for the Biological Version of Oja’s Rule in Solving Streaming PCA COLT 2020 On the Power of Compressed Sensing with Generative Models ICML 2020 Partial Trace Regression and Low-Rank Kraus Decomposition ICML 2020 Precise expressions for random projections: Low-rank approximation and randomized Newton NeurIPS 2020 pyDML: A Python Library for Distance Metric Learning JMLR 2020 Quantitative stability of optimal transport maps and linearization of the 2-Wasserstein space AISTATS 2020 Random Projections and α-Shape to Support the Kernel Design (Student Abstract) AAAI 2020 Ratio Trace Formulation of Wasserstein Discriminant Analysis NeurIPS 2020 Recent Developments in Boolean Matrix Factorization IJCAI 2020 Regularized Estimation of High-dimensional Factor-Augmented Vector Autoregressive (FAVAR) Models JMLR 2020 Revisiting the Sample Complexity of Sparse Spectrum Approximation of Gaussian Processes NeurIPS 2020 Robust Tensor Decomposition via Orientation Invariant Tubal Nuclear Norms AAAI 2020 Scaling up Simhash ACML 2020 Steering Distortions to Preserve Classes and Neighbors in Supervised Dimensionality Reduction NeurIPS 2020 Stochastic Sparse Subspace Clustering CVPR 2020 The Maximum Separation Subspace in Sufficient Dimension Reduction with Categorical Response JMLR 2020 Union of Low-Rank Tensor Spaces: Clustering and Completion JMLR 2020 Active Sampling for Open-Set Classification without Initial Annotation AAAI 2019 A Kernel Random Matrix-Based Approach for Sparse PCA ICLR 2019 Analytical Methods for Interpretable Ultradense Word Embeddings EMNLP 2019 A Nonconvex Projection Method for Robust PCA AAAI 2019 Complex Moment-Based Supervised Eigenmap for Dimensionality Reduction AAAI 2019 Dimensionality Reduction and (Bucket) Ranking: a Mass Transportation Approach ALT 2019