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 3941–3950 of 4891 papers

TitleStatusHype
Learning to Generate Content-Aware Dynamic Detectors—0
EXTENDING CONDITIONAL CONVOLUTION STRUCTURES FOR ENHANCING MULTITASKING CONTINUAL LEARNINGCode1
IHashNet: Iris Hashing Network based on efficient multi-index hashing—0
Linear Reduced Order Model Predictive ControlCode1
A Hierarchical Deep Actor-Critic Learning Method for Joint Distribution System State Estimation—0
Forecast with Forecasts: Diversity Matters—0
Gaussian Process-based Approach for Bilevel Optimization in the Power System -- A Critical Load Restoration Case—0
Towards Fast and Accurate Neural Chinese Word Segmentation with Multi-Criteria Learning—0
On Efficiency in Hierarchical Reinforcement Learning—0
Efficient Assessment of Electricity Distribution Network Adequacy with the Cross-Entropy Method—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified