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 3521–3530 of 4891 papers

TitleStatusHype
An Efficient Speech Separation Network Based on Recurrent Fusion Dilated Convolution and Channel Attention—0
An Empirical Analysis of Speech Self-Supervised Learning at Multiple Resolutions—0
An Empirical Study of Dimensional Reduction Techniques for Facial Action Units Detection—0
An Empirical Study of Training State-of-the-Art LiDAR Segmentation Models—0
An Energy-efficient Aerial Backhaul System with Reconfigurable Intelligent Surface—0
An Enhanced Low-Resolution Image Recognition Method for Traffic Environments—0
An Enhancement of CNN Algorithm for Rice Leaf Disease Image Classification in Mobile Applications—0
An Enhancement of Jiang, Z., et al.s Compression-Based Classification Algorithm Applied to News Article Categorization—0
A Neural Network Subgrid Model of the Early Stages of Planet Formation—0
An even-load-distribution design for composite bolted joints using a novel circuit model and artificial neural networks—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified