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 4161–4170 of 4891 papers

TitleStatusHype
Instability, Computational Efficiency and Statistical Accuracy—0
Beyond the Mean-Field: Structured Deep Gaussian Processes Improve the Predictive UncertaintiesCode0
Optimal Distributed Subsampling for Maximum Quasi-Likelihood Estimators with Massive Data—0
MOTS: Multiple Object Tracking for General Categories Based On Few-Shot Method—0
An Efficient Machine-Learning Approach for PDF Tabulation in Turbulent Combustion Closure—0
Speech to Text Adaptation: Towards an Efficient Cross-Modal Distillation—0
Convolutional Neural Network for emotion recognition to assist psychiatrists and psychologists during the COVID-19 pandemic: experts opinion—0
Visual Perception Model for Rapid and Adaptive Low-light Image Enhancement—0
Walking with Perception: Efficient Random Walk Sampling via Common Neighbor Awareness—0
Accelerating Deep Neuroevolution on Distributed FPGAs for Reinforcement Learning Problems—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified