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Sparse Optimization

347 directly classified papers

Papers per year

Papers

Projected Gradient Descent Algorithms for Solving Nonlinear Inverse Problems with Generative Priors IJCAI 2022
abess: A Fast Best-Subset Selection Library in Python and R JMLR 2022
The Geometry of Uniqueness, Sparsity and Clustering in Penalized Estimation JMLR 2022
Noisy L0-sparse subspace clustering on dimensionality reduced data UAI 2022
tntorch: Tensor Network Learning with PyTorch JMLR 2022
Anisotropic Additive Quantization for Fast Inner Product Search AAAI 2022
Zeroth-Order Hard-Thresholding: Gradient Error vs. Expansivity NIPS 2022
Sparse and Smooth Signal Estimation: Convexification of L0-Formulations JMLR 2021
Dual Principal Component Pursuit for Robust Subspace Learning: Theory and Algorithms for a Holistic Approach ICML 2021
Soft Tensor Regression JMLR 2021
Regularized Submodular Maximization at Scale ICML 2021
Expanding Boundaries of Gap Safe Screening JMLR 2021
Homomorphic Sensing: Sparsity and Noise ICML 2021
Inferring serial correlation with dynamic backgrounds ICML 2021
Approximate Multiplication of Sparse Matrices with Limited Space AAAI 2021
Distributed Machine Learning with Sparse Heterogeneous Data NIPS 2021
Low-Rank Registration Based Manifolds for Convection-Dominated PDEs AAAI 2021
A Note on Sparse Generalized Eigenvalue Problem NIPS 2021
Support Recovery of Sparse Signals from a Mixture of Linear Measurements NIPS 2021
General Low-rank Matrix Optimization: Geometric Analysis and Sharper Bounds NIPS 2021
Global and Quadratic Convergence of Newton Hard-Thresholding Pursuit JMLR 2021
Revitalizing Optimization for 3D Human Pose and Shape Estimation: A Sparse Constrained Formulation ICCV 2021
Low-Rank Tensor Completion by Approximating the Tensor Average Rank ICCV 2021
A Nullspace Property for Subspace-Preserving Recovery ICML 2021
Sparse Feature Selection Makes Batch Reinforcement Learning More Sample Efficient ICML 2021