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 3511–3520 of 4891 papers

TitleStatusHype
BlazeNeo: Blazing fast polyp segmentation and neoplasm detectionCode0
A Robust Multimodal Remote Sensing Image Registration Method and System Using Steerable Filters with First- and Second-order Gradients—0
Residual Bootstrap Exploration for Stochastic Linear Bandit—0
CD-ROM: Complemented Deep-Reduced Order Model—0
HoneyModels: Machine Learning Honeypots—0
Deep Learning for Hate Speech Detection: A Comparative StudyCode1
FinNet: Solving Time-Independent Differential Equations with Finite Difference Neural NetworkCode0
GRAPHSHAP: Explaining Identity-Aware Graph Classifiers Through the Language of Motifs—0
Guidelines and Evaluation of Clinical Explainable AI in Medical Image AnalysisCode1
Fast Inverter Control by Learning the OPF Mapping using Sensitivity-Informed Gaussian Processes—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified