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 4201–4210 of 4891 papers

TitleStatusHype
A Deep Learning Algorithm for High-Dimensional Exploratory Item Factor Analysis—0
Fast Sequence-Based Embedding with Diffusion GraphsCode1
P^2-GAN: Efficient Style Transfer Using Single Style ImageCode0
Context-Aware Cross-Attention for Skeleton-Based Human Action Recognition—0
On the Trend-corrected Variant of Adaptive Stochastic Optimization Methods—0
A lightweight target detection algorithm based on Mobilenet Convolution—0
Adaptive Direction-Guided Structure Tensor Total Variation—0
The gap between theory and practice in function approximation with deep neural networksCode1
One-Shot Coordination of First and Last Mode Transportation—0
Online Continual Learning from Imbalanced Data—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified