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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 2991–3000 of 4891 papers

TitleStatusHype
The Deep Promotion Time Cure ModelCode0
Nonconvex Robust High-Order Tensor Completion Using Randomized Low-Rank Approximation—0
Efficient ConvBN Blocks for Transfer Learning and BeyondCode1
Time Series Clustering With Random Convolutional KernelsCode0
CageViT: Convolutional Activation Guided Efficient Vision Transformer—0
DualFL: A Duality-based Federated Learning Algorithm with Communication Acceleration in the General Convex Regime—0
Principal Uncertainty Quantification with Spatial Correlation for Image Restoration ProblemsCode1
Smooth Robustness Measures for Symbolic Control Via Signal Temporal Logic—0
Benchmarking the human brain against computational architectures—0
Neural information coding for efficient spike-based image denoising—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified