Co-occurring keywords · papers mentioning both
Papers
Schur's Positive-Definite Network: Deep Learning in the SPD cone with structure
ICLR 2025
Dimension-free Structured Covariance Estimation
COLT 2024
Model-free Low-Rank Reinforcement Learning via Leveraged Entry-wise Matrix Estimation
NeurIPS 2024
Learning the Positions in CountSketch
ICLR 2023
MARS: A Second-Order Reduction Algorithm for High-Dimensional Sparse Precision Matrices Estimation
JMLR 2023
Matrix Estimation for Individual Fairness
ICML 2023
Spectral Entry-wise Matrix Estimation for Low-Rank Reinforcement Learning
NeurIPS 2023
Differentially Private Covariance Revisited
NeurIPS 2022
On Low-rank Trace Regression under General Sampling Distribution
JMLR 2022
Recovering shared structure from multiple networks with unknown edge distributions
JMLR 2022
A heuristic for statistical seriation
UAI 2021
Linear Convergence of Gradient Methods for Estimating Structured Transition Matrices in High-dimensional Vector Autoregressive Models
NeurIPS 2021
Rank-one matrix estimation: analytic time evolution of gradient descent dynamics
COLT 2021
Harnessing Structures for Value-Based Planning and Reinforcement Learning
ICLR 2020
Sample Efficient Reinforcement Learning via Low-Rank Matrix Estimation
NeurIPS 2020
Affine Invariant Covariance Estimation for Heavy-Tailed Distributions
COLT 2019
ME-Net: Towards Effective Adversarial Robustness with Matrix Estimation
ICML 2019
On Robustness of Principal Component Regression
NeurIPS 2019
A Fast and Scalable Joint Estimator for Integrating Additional Knowledge in Learning Multiple Related Sparse Gaussian Graphical Models
ICML 2018
Breaking the 1/√n Barrier: Faster Rates for Permutation-based Models in Polynomial Time
COLT 2018
Sketched Ridge Regression: Optimization Perspective, Statistical Perspective, and Model Averaging
JMLR 2018
Adaptive Clustering through Semidefinite Programming
NeurIPS 2017
Matrix Norm Estimation from a Few Entries
NeurIPS 2017
Minimax Estimation of Bandable Precision Matrices
NeurIPS 2017
On Approximation Guarantees for Greedy Low Rank Optimization
ICML 2017