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 4131–4140 of 4891 papers

TitleStatusHype
Similarity Search for Efficient Active Learning and Search of Rare Concepts—0
Variational Autoencoding of PDE Inverse Problems—0
Localization Uncertainty Estimation for Anchor-Free Object Detection—0
Differential Privacy of Hierarchical Census Data: An Optimization Approach—0
DRACO: Co-Optimizing Hardware Utilization, and Performance of DNNs on Systolic Accelerator—0
Recurrent Relational Memory Network for Unsupervised Image Captioning—0
Coordination of OLTC and Smart Inverters for Optimal Voltage Regulation of Unbalanced Distribution Networks—0
Accelerated Deep Reinforcement Learning Based Load Shedding for Emergency Voltage Control—0
Gradient-EM Bayesian Meta-learning—0
A deep convolutional neural network model for rapid prediction of fluvial flood inundation—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified