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 3311–3320 of 4891 papers

TitleStatusHype
Accelerating Spherical k-Means—0
Accelerating Text Mining Using Domain-Specific Stop Word Lists—0
Accelerating the discovery of low-energy structure configurations: a computational approach that integrates first-principles calculations, Monte Carlo sampling, and Machine Learning—0
Accelerating the Evolution of Personalized Automated Lane Change through Lesson Learning—0
Acceleration and Parallelization Methods for ISRS EGN Model—0
Sparse solutions of the kernel herding algorithm by improved gradient approximation—0
Accumulations of Projections--A Unified Framework for Random Sketches in Kernel Ridge Regression—0
Accurate and scalable exchange-correlation with deep learning—0
Accurate Hand Keypoint Localization on Mobile Devices—0
A Chaining Algorithm for Online Nonparametric Regression—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified