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Sparse Learning

Papers

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Showing 151–185 of 185 papers

TitleStatusHype
Efficient Distributed Learning with Sparsity—0
Nonconvex Sparse Learning via Stochastic Optimization with Progressive Variance Reduction—0
On the exact recovery of sparse signals via conic relaxations—0
Feature Selection: A Data PerspectiveCode0
Universal Collaboration Strategies for Signal Detection: A Sparse Learning Approach—0
HONOR: Hybrid Optimization for NOn-convex Regularized problems—0
Sparse learning of maximum likelihood model for optimization of complex loss function—0
Sparse Learning for Large-scale and High-dimensional Data: A Randomized Convex-concave Optimization Approach—0
Parametric Maxflows for Structured Sparse Learning with Convex Relaxations of Submodular Functions—0
Best Subset Selection via a Modern Optimization Lens—0
Safe Feature Pruning for Sparse High-Order Interaction Models—0
Direct l_(2,p)-Norm Learning for Feature Selection—0
A Nonconvex Approach for Structured Sparse Learning—0
Statistical Limits of Convex Relaxations—0
Pathwise Coordinate Optimization for Sparse Learning: Algorithm and Theory—0
Accelerated Mini-batch Randomized Block Coordinate Descent Method—0
Partial Occlusion Handling for Visual Tracking via Robust Part Matching—0
A Distributed Frank-Wolfe Algorithm for Communication-Efficient Sparse Learning—0
Beyond L2-Loss Functions for Learning Sparse Models—0
Sparse Learning over Infinite Subgraph Features—0
Can Image-Level Labels Replace Pixel-Level Labels for Image Parsing—0
Tensor Representation and Manifold Learning Methods for Remote Sensing Images—0
Safe and Efficient Screening For Sparse Support Vector Machine—0
Compound Poisson Processes, Latent Shrinkage Priors and Bayesian Nonconvex Penalization—0
Safe Screening With Variational Inequalities and Its Application to LASSO—0
Efficient Mixed-Norm Regularization: Algorithms and Safe Screening Methods—0
Multi-task Sparse Learning with Beta Process Prior for Action Recognition—0
A General Iterative Shrinkage and Thresholding Algorithm for Non-convex Regularized Optimization ProblemsCode0
Approximate Message Passing with Consistent Parameter Estimation and Applications to Sparse Learning—0
Accelerated Training for Matrix-norm Regularization: A Boosting Approach—0
EigenNet: A Bayesian hybrid of generative and conditional models for sparse learning—0
Non-parametric Group Orthogonal Matching Pursuit for Sparse Learning with Multiple Kernels—0
Multivariate Dyadic Regression Trees for Sparse Learning Problems—0
Nonparametric Greedy Algorithms for the Sparse Learning Problem—0
Adaptive Forward-Backward Greedy Algorithm for Sparse Learning with Linear Models—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