SOTAVerified

Sparse Learning

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 26–50 of 185 papers

TitleStatusHype
Best Subset Selection with Efficient Primal-Dual Algorithm—0
Beyond L2-Loss Functions for Learning Sparse Models—0
Best Subset Selection via a Modern Optimization Lens—0
AMS-Net: Adaptive Multiscale Sparse Neural Network with Interpretable Basis Expansion for Multiphase Flow Problems—0
Can Image-Level Labels Replace Pixel-Level Labels for Image Parsing—0
A bio-inspired implementation of a sparse-learning spike-based hippocampus memory model—0
Bayesian Sparse learning with preconditioned stochastic gradient MCMC and its applications—0
Direct l_(2,p)-Norm Learning for Feature Selection—0
Automatically Redundant Features Removal for Unsupervised Feature Selection via Sparse Feature Graph—0
Efficient Distributed Learning with Sparsity—0
EigenNet: A Bayesian hybrid of generative and conditional models for sparse learning—0
A unified approach to mixed-integer optimization problems with logical constraints—0
A Distributed Frank-Wolfe Algorithm for Communication-Efficient Sparse Learning—0
Accelerated Training for Matrix-norm Regularization: A Boosting Approach—0
CRB Analysis for Mixed-ADC Based DOA Estimation—0
Approximate Message Passing with Consistent Parameter Estimation and Applications to Sparse Learning—0
Concise Fuzzy System Modeling Integrating Soft Subspace Clustering and Sparse Learning—0
A Sparse Learning Approach to the Design of Radar Tunable Architectures with Enhanced Selectivity Properties—0
Dantzig Selector with an Approximately Optimal Denoising Matrix and its Application to Reinforcement Learning—0
Decentralized Frank-Wolfe Algorithm for Convex and Non-convex Problems—0
Deep Weight Factorization: Sparse Learning Through the Lens of Artificial Symmetries—0
Nonparametric Sparse Online Learning of the Koopman Operator—0
Discovering stochastic partial differential equations from limited data using variational Bayes inference—0
A Data-Driven Sparse-Learning Approach to Model Reduction in Chemical Reaction Networks—0
Dynamic Sparse Learning: A Novel Paradigm for Efficient Recommendation—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