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 2761–2770 of 4891 papers

TitleStatusHype
Single-level Robust Bidding of Renewable-only Virtual Power Plant in Energy and Ancillary Service Markets for Worst-case Profit—0
Singleshot : a scalable Tucker tensor decomposition—0
Single Target Tracking Using Adaptive Clustered Decision Trees and Dynamic Multi-Level Appearance Models—0
Sinusoidal Parameter Estimation from Signed Measurements via Majorization-Minimization Based RELAX—0
Skeleton-based Human Action Recognition via Convolutional Neural Networks (CNN)—0
Sketch and Validate for Big Data Clustering—0
TMHOI: Translational Model for Human-Object Interaction Detection—0
SkillFormer: Unified Multi-View Video Understanding for Proficiency Estimation—0
SLCGC: A lightweight Self-supervised Low-pass Contrastive Graph Clustering Network for Hyperspectral Images—0
Slimming Down LLMs Without Losing Their Minds—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified