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sparse optimization

246 papers

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Co-occurring keywords

convex optimization (1321) feature selection (649) sparse regression (175) compressed sensing (201) l1 regularization (87) sparse representation (297) graphical model (864) dimensionality reduction (720) model compression (3302) support vector machine (978)

Papers

Low Resource Quadratic Forms for Knowledge Graph Embeddings EMNLP 2021
Square Root Bundle Adjustment for Large-Scale Reconstruction CVPR 2021
Efficient On-Chip Learning for Optical Neural Networks Through Power-Aware Sparse Zeroth-Order Optimization AAAI 2021
A Novel Sequential Coreset Method for Gradient Descent Algorithms ICML 2021
Revitalizing Optimization for 3D Human Pose and Shape Estimation: A Sparse Constrained Formulation ICCV 2021
Dynamic Sasvi: Strong Safe Screening for Norm-Regularized Least Squares NIPS 2021
Stochastic Proximal Methods for Non-Smooth Non-Convex Constrained Sparse Optimization JMLR 2021
Homomorphic Sensing: Sparsity and Noise ICML 2021
Sparse Quadratic Optimisation over the Stiefel Manifold with Application to Permutation Synchronisation NIPS 2021
Distributed Machine Learning with Sparse Heterogeneous Data NIPS 2021
Global and Quadratic Convergence of Newton Hard-Thresholding Pursuit JMLR 2021
Sparse Multi-Path Corrections in Fringe Projection Profilometry CVPR 2021
Sparse and Smooth Signal Estimation: Convexification of L0-Formulations JMLR 2021
The Flip Side of the Reweighted Coin: Duality of Adaptive Dropout and Regularization NIPS 2021
Expanding Boundaries of Gap Safe Screening JMLR 2021
Neural Architecture Search as Sparse Supernet AAAI 2021
Learning Set Functions that are Sparse in Non-Orthogonal Fourier Bases AAAI 2021
A Note on Sparse Generalized Eigenvalue Problem NIPS 2021
Variational Pathway Reasoning for EEG Emotion Recognition AAAI 2020
Sparse Optimization for Unsupervised Extractive Summarization of Long Documents with the Frank-Wolfe Algorithm EMNLP 2020
Learning Feature Sparse Principal Subspace NIPS 2020
High-dimensional Gaussian graphical models on network-linked data JMLR 2020
High Dimensional Forecasting via Interpretable Vector Autoregression JMLR 2020
Cogradient Descent for Bilinear Optimization CVPR 2020
On the Theoretical Guarantees for Parameter Estimation of Gaussian Random Field Models: A Sparse Precision Matrix Approach JMLR 2020