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 4311–4320 of 4891 papers

TitleStatusHype
Bayesian Spatial Field Reconstruction with Unknown Distortions in Sensor Networks—0
A Cooperative Autoencoder for Population-Based Regularization of CNN Image Registration—0
A Machine Learning Based Classification Approach for Power Quality Disturbances Exploiting Higher Order Statistics in the EMD Domain—0
Least Squares Approximation for a Distributed SystemCode0
A Fast Spectral Algorithm for Mean Estimation with Sub-Gaussian Rates—0
Point-Based Multi-View Stereo NetworkCode0
Continual Learning via Online Leverage Score Sampling—0
Towards a Theory of Intentions for Human-Robot Collaboration—0
LYTNet: A Convolutional Neural Network for Real-Time Pedestrian Traffic Lights and Zebra Crossing Recognition for the Visually ImpairedCode0
Real-Time Correlation Tracking via Joint Model Compression and TransferCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified