SOTAVerified

Sparse Learning

Papers

Showing 150 of 185 papers

TitleStatusHype
Event Enhanced High-Quality Image RecoveryCode1
Sparse Regression at Scale: Branch-and-Bound rooted in First-Order OptimizationCode1
APP: Anytime Progressive PruningCode1
Scalable Training of Artificial Neural Networks with Adaptive Sparse Connectivity inspired by Network ScienceCode1
Sparse Training via Boosting Pruning Plasticity with NeuroregenerationCode1
The State of Sparsity in Deep Neural NetworksCode1
SLTrain: a sparse plus low-rank approach for parameter and memory efficient pretrainingCode1
Learning to Super-Resolve Blurry Images with EventsCode1
Picasso: A Sparse Learning Library for High Dimensional Data Analysis in R and PythonCode1
Variational Dropout Sparsifies Deep Neural NetworksCode1
abess: A Fast Best Subset Selection Library in Python and RCode1
Block-wise Minimization-Majorization algorithm for Huber's criterion: sparse learning and applicationsCode1
Sparse Weight Activation TrainingCode1
Sparse Networks from Scratch: Faster Training without Losing PerformanceCode1
Fast Best Subset Selection: Coordinate Descent and Local Combinatorial Optimization AlgorithmsCode1
Do We Actually Need Dense Over-Parameterization? In-Time Over-Parameterization in Sparse TrainingCode1
Rigging the Lottery: Making All Tickets WinnersCode1
Controlled Sparsity via Constrained Optimization or: How I Learned to Stop Tuning Penalties and Love ConstraintsCode1
Learning where to learn: Gradient sparsity in meta and continual learningCode1
Block Sparse Bayesian Learning: A Diversified SchemeCode1
AdaMix: Mixture-of-Adaptations for Parameter-efficient Model TuningCode1
L0Learn: A Scalable Package for Sparse Learning using L0 RegularizationCode1
ssProp: Energy-Efficient Training for Convolutional Neural Networks with Scheduled Sparse Back PropagationCode0
DRFormer: Multi-Scale Transformer Utilizing Diverse Receptive Fields for Long Time-Series ForecastingCode0
Subset Selection with Shrinkage: Sparse Linear Modeling when the SNR is lowCode0
Sparse learning of stochastic dynamic equationsCode0
A graph-embedded deep feedforward network for disease outcome classification and feature selection using gene expression dataCode0
A General Iterative Shrinkage and Thresholding Algorithm for Non-convex Regularized Optimization ProblemsCode0
Building explainable graph neural network by sparse learning for the drug-protein binding predictionCode0
Similarity Preserving Unsupervised Feature Selection based on Sparse LearningCode0
SL-CycleGAN: Blind Motion Deblurring in Cycles using Sparse LearningCode0
Probabilistic Iterative Hard Thresholding for Sparse LearningCode0
Cross-Modal Ranking with Soft Consistency and Noisy Labels for Robust RGB-T TrackingCode0
RobustTrend: A Huber Loss with a Combined First and Second Order Difference Regularization for Time Series Trend FilteringCode0
Optimal approximation for unconstrained non-submodular minimizationCode0
MyESL: Sparse learning in molecular evolution and phylogenetic analysisCode0
Scalable Subset Selection in Linear Mixed ModelsCode0
Accelerated Gradient Methods for Sparse Statistical Learning with Nonconvex PenaltiesCode0
HyperSparse Neural Networks: Shifting Exploration to Exploitation through Adaptive RegularizationCode0
KNN Classification with One-step ComputationCode0
Collaborative Preference Embedding against Sparse LabelsCode0
CLASSP: a Biologically-Inspired Approach to Continual Learning through Adjustment Suppression and Sparsity PromotionCode0
Grouped Variable Selection with Discrete Optimization: Computational and Statistical PerspectivesCode0
Optimizing Rare Word Accuracy in Direct Speech Translation with a Retrieval-and-Demonstration ApproachCode0
Feature Selection: A Data PerspectiveCode0
Resource Constrained Model Compression via Minimax Optimization for Spiking Neural NetworksCode0
Fast OSCAR and OWL Regression via Safe Screening RulesCode0
Lottery Aware Sparsity Hunting: Enabling Federated Learning on Resource-Limited EdgeCode0
From safe screening rules to working sets for faster Lasso-type solversCode0
Learning task structure via sparsity grouped multitask learningCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Resnet-50: 80% SparseTop-1 Accuracy77.1Unverified
2Resnet-50: 90% SparseTop-1 Accuracy76.4Unverified
3Resnet-50: 80% Sparse 100 epochsTop-1 Accuracy76Unverified
4Resnet-50: 80% Sparse 100 epochsTop-1 Accuracy75.84Unverified
5Resnet-50: 90% Sparse 100 epochsTop-1 Accuracy74.5Unverified
6Resnet-50: 90% Sparse 100 epochsTop-1 Accuracy73.82Unverified
7MobileNet-v1: 75% SparseTop-1 Accuracy71.9Unverified
8MobileNet-v1: 90% SparseTop-1 Accuracy68.1Unverified
9SINDyTop-1 Accuracy6Unverified
#ModelMetricClaimedVerifiedStatus
1Resnet18Sparsity92.43Unverified
#ModelMetricClaimedVerifiedStatus
1Resnet18Sparsity93.63Unverified