SOTAVerified

Computational Efficiency

Methods and optimizations to reduce the computational resources (e.g., time, memory, or power) needed for training and inference in models. This involves techniques that streamline processing, optimize algorithms, or leverage hardware to enhance performance without compromising accuracy.

Papers

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Showing 3711–3720 of 4891 papers

TitleStatusHype
Deep convolutional neural network for shape optimization using level-set approachCode0
An MRC Framework for Semantic Role Labeling—0
Recursive Least Squares Advantage Actor-Critic Algorithms—0
Study of Frequency domain exponential functional link network filters—0
Auction-Based Ex-Post-Payment Incentive Mechanism Design for Horizontal Federated Learning with Reputation and Contribution Measurement—0
Jointly Efficient and Optimal Algorithms for Logistic BanditsCode0
Quality-aware Part Models for Occluded Person Re-identification—0
Electric Field Models of Transcranial Magnetic Stimulation Coils with Arbitrary Geometries: Reconstruction from Incomplete Magnetic Field MeasurementsCode0
Data-Driven Outage Restoration Time Prediction via Transfer Learning with Cluster Ensembles—0
Robust Data-Driven Linear Power Flow Model with Probability Constrained Worst-Case Errors—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified