Co-occurring keywords · papers mentioning both
Papers
Provable Guarantees For Robust Feature Selection in Sparse Linear Models in High-Dimensions
UAI 2026
Robust Score Matching
AISTATS 2025
Simplex Constrained Sparse Optimization via Tail Screening
JMLR 2025
Distributed High-Dimensional Quantile Regression: Estimation Efficiency and Support Recovery
ICML 2024
Recovery Guarantees for Distributed-OMP
AISTATS 2024
Straight-Through Meets Sparse Recovery: the Support Exploration Algorithm
ICML 2024
Support Recovery in Sparse PCA with General Missing Data
UAI 2024
Average case analysis of Lasso under ultra sparse conditions
AISTATS 2023
Learning Sparse Group Models Through Boolean Relaxation
ICLR 2023
Statistical-Computational Tradeoffs in Mixed Sparse Linear Regression
COLT 2023
Byzantine-tolerant distributed multiclass sparse linear discriminant analysis
UAI 2022
Entrywise Recovery Guarantees for Sparse PCA via Sparsistent Algorithms
AISTATS 2022
Label noise (stochastic) gradient descent implicitly solves the Lasso for quadratic parametrisation
COLT 2022
On Learning Mixture Models with Sparse Parameters
AISTATS 2022
Support Recovery in Sparse PCA with Incomplete Data
NeurIPS 2022
Efficient Statistics for Sparse Graphical Models from Truncated Samples
AISTATS 2021
Hadamard Wirtinger Flow for Sparse Phase Retrieval
AISTATS 2021
Meta Learning for Support Recovery in High-dimensional Precision Matrix Estimation
ICML 2021
On learning sparse vectors from mixture of responses
NeurIPS 2021
Support Recovery of Sparse Signals from a Mixture of Linear Measurements
NeurIPS 2021
The Sample Complexity of Meta Sparse Regression
AISTATS 2021
Distributed High-dimensional Regression Under a Quantile Loss Function
JMLR 2020
Information Theoretic Optimal Learning of Gaussian Graphical Models
COLT 2020
One-Bit Compressed Sensing via One-Shot Hard Thresholding
UAI 2020
Interplay of minimax estimation and minimax support recovery under sparsity
ALT 2019