SOTAVerified

Sparse Learning

Papers

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Showing 101–125 of 185 papers

TitleStatusHype
Safe Feature Pruning for Sparse High-Order Interaction Models—0
Safe Screening With Variational Inequalities and Its Application to LASSO—0
Scaling Continuous Kernels with Sparse Fourier Domain Learning—0
A Discriminative Gaussian Mixture Model with Sparsity—0
Simultaneous Clustering and Estimation of Heterogeneous Graphical Models—0
Sketching for Convex and Nonconvex Regularized Least Squares with Sharp Guarantees—0
Smoothing the Edges: Smooth Optimization for Sparse Regularization using Hadamard Overparametrization—0
Sparse Learning and Class Probability Estimation with Weighted Support Vector Machines—0
Sparse Learning for Large-scale and High-dimensional Data: A Randomized Convex-concave Optimization Approach—0
Sparse Learning for Variable Selection with Structures and Nonlinearities—0
Structure learning via unstructured kernel-based M-regression—0
Sparse learning of maximum likelihood model for optimization of complex loss function—0
Sparse Learning over Infinite Subgraph Features—0
Sparse learning with CART—0
Sparse Range-constrained Learning and Its Application for Medical Image Grading—0
Sparse Representer Theorems for Learning in Reproducing Kernel Banach Spaces—0
Sparsified-Learning for Heavy-Tailed Locally Stationary Processes—0
Sparsifying Binary Networks—0
STARS: Sparse Learning Correlation Filter with Spatio-temporal Regularization and Super-resolution Reconstruction for Thermal Infrared Target Tracking—0
Statistical Limits of Convex Relaxations—0
Strongly Hierarchical Factorization Machines and ANOVA Kernel Regression—0
Structure-preserving Guided Retinal Image Filtering and Its Application for Optic Disc Analysis—0
SuperGF: Unifying Local and Global Features for Visual Localization—0
Super-sparse Learning in Similarity Spaces—0
Surrogate assisted active subspace and active subspace assisted surrogate -- A new paradigm for high dimensional structural reliability analysis—0
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All datasetsImageNetCINIC-10ImageNet32

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Resnet-50: 80% SparseTop-1 Accuracy77.1—Unverified
2Resnet-50: 90% SparseTop-1 Accuracy76.4—Unverified
3Resnet-50: 80% Sparse 100 epochsTop-1 Accuracy76—Unverified
4Resnet-50: 80% Sparse 100 epochsTop-1 Accuracy75.84—Unverified
5Resnet-50: 90% Sparse 100 epochsTop-1 Accuracy74.5—Unverified
6Resnet-50: 90% Sparse 100 epochsTop-1 Accuracy73.82—Unverified
7MobileNet-v1: 75% SparseTop-1 Accuracy71.9—Unverified
8MobileNet-v1: 90% SparseTop-1 Accuracy68.1—Unverified
9SINDyTop-1 Accuracy6—Unverified
#ModelMetricClaimedVerifiedStatus
1Resnet18Sparsity92.43—Unverified
#ModelMetricClaimedVerifiedStatus
1Resnet18Sparsity93.63—Unverified