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Sparse Optimization

95 directly classified papers

Papers per year

Papers

Robust group and simultaneous inferences for high-dimensional single index model NIPS 2024
Oja's Algorithm for Streaming Sparse PCA NIPS 2024
Fast Iterative Hard Thresholding Methods with Pruning Gradient Computations NIPS 2024
Recovery Guarantees for Distributed-OMP AISTATS 2024
A minimax optimal approach to high-dimensional double sparse linear regression JMLR 2024
The Emergence of Essential Sparsity in Large Pre-trained Models: The Weights that Matter NIPS 2023
Dynamic Low-rank Estimation for Transformer-based Language Models EMNLP 2023
Data-Efficient Structured Pruning via Submodular Optimization NIPS 2022
Signal Recovery with Non-Expansive Generative Network Priors NIPS 2022
Global Linear and Local Superlinear Convergence of IRLS for Non-Smooth Robust Regression NIPS 2022
Towards Fully Sparse Training: Information Restoration with Spatial Similarity AAAI 2022
Fast Algorithm for Low-Rank Tensor Completion in Delay-Embedded Space CVPR 2022
Zeroth-Order Hard-Thresholding: Gradient Error vs. Expansivity NIPS 2022
Learning Set Functions that are Sparse in Non-Orthogonal Fourier Bases AAAI 2021
Learning Compositional Sparse Gaussian Processes with a Shrinkage Prior AAAI 2021
Sample-Efficient L0-L2 Constrained Structure Learning of Sparse Ising Models AAAI 2021
Dynamic Sasvi: Strong Safe Screening for Norm-Regularized Least Squares NIPS 2021
Stochastic Sparse Subspace Clustering CVPR 2020
Factor Group-Sparse Regularization for Efficient Low-Rank Matrix Recovery NIPS 2019
Graphical Lasso and Thresholding: Equivalence and Closed-form Solutions JMLR 2019
Algorithmic Analysis and Statistical Estimation of SLOPE via Approximate Message Passing NIPS 2019
RS3CIS: Robust Single-Step Spectral Clustering with Intrinsic Subspace AAAI 2019
Sparse High-Dimensional Isotonic Regression NIPS 2019
The Impact of Regularization on High-dimensional Logistic Regression NIPS 2019
Learning Sparse Distributions using Iterative Hard Thresholding NIPS 2019