Sparse Optimization

Learning Sparse Group Models Through Boolean Relaxation ICLR 2023 OKRidge: Scalable Optimal k-Sparse Ridge Regression NeurIPS 2023 Open Problem: Learning sparse linear concepts by priming the features COLT 2023 Statistical-Computational Tradeoffs in Mixed Sparse Linear Regression COLT 2023 The Emergence of Essential Sparsity in Large Pre-trained Models: The Weights that Matter NeurIPS 2023 Beyond L1: Faster and Better Sparse Models with skglm NeurIPS 2022 Chunk Dynamic Updating for Group Lasso with ODEs AAAI 2022 Data-Efficient Structured Pruning via Submodular Optimization NeurIPS 2022 Debiased Distributed Learning for Sparse Partial Linear Models in High Dimensions JMLR 2022 Discovering Interpretable Data-to-Sequence Generators AAAI 2022 Fast Algorithm for Low-Rank Tensor Completion in Delay-Embedded Space CVPR 2022 Global Linear and Local Superlinear Convergence of IRLS for Non-Smooth Robust Regression NeurIPS 2022 Open Problem: Running time complexity of accelerated ℓ_1-regularized PageRank COLT 2022 Pruning Neural Networks via Coresets and Convex Geometry: Towards No Assumptions NeurIPS 2022 Robust Estimation of Laplacian Constrained Gaussian Graphical Models with Trimmed Non-convex Regularization PGM 2022 Signal Recovery with Non-Expansive Generative Network Priors NeurIPS 2022 The Hessian Screening Rule NeurIPS 2022 Towards Fully Sparse Training: Information Restoration with Spatial Similarity AAAI 2022 Zeroth-Order Hard-Thresholding: Gradient Error vs. Expansivity NeurIPS 2022 Dynamic Sasvi: Strong Safe Screening for Norm-Regularized Least Squares NeurIPS 2021 Learning Compositional Sparse Gaussian Processes with a Shrinkage Prior AAAI 2021 Learning Set Functions that are Sparse in Non-Orthogonal Fourier Bases AAAI 2021 On InstaHide, Phase Retrieval, and Sparse Matrix Factorization ICLR 2021 Sample-Efficient L0-L2 Constrained Structure Learning of Sparse Ising Models AAAI 2021 Deeply Learned Spectral Total Variation Decomposition NeurIPS 2020