reduced-rank regression

LoRANN: Low-Rank Matrix Factorization for Approximate Nearest Neighbor Search NeurIPS 2024 Sharp Spectral Rates for Koopman Operator Learning NeurIPS 2023 Learning Dynamical Systems via Koopman Operator Regression in Reproducing Kernel Hilbert Spaces NeurIPS 2022 Vector-Valued Least-Squares Regression under Output Regularity Assumptions JMLR 2022 Reduced-Rank Regression with Operator Norm Error COLT 2021 Adaptive Reduced Rank Regression NeurIPS 2020 A simple normative network approximates local non-Hebbian learning in the cortex NeurIPS 2020 Implicit Regularization of Discrete Gradient Dynamics in Linear Neural Networks NeurIPS 2019 Scalable Interpretable Multi-Response Regression via SEED JMLR 2019 Multiple Output Regression with Latent Noise JMLR 2016 Bayesian inference for low rank spatiotemporal neural receptive fields NeurIPS 2013 Nonlinear low-dimensional regression using auxiliary coordinates AISTATS 2012 Nonparametric Reduced Rank Regression NeurIPS 2012 Learning low-rank output kernels ACML 2011 Learning omnidirectional path following using dimensionality reduction RSS 2007