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 3701–3710 of 4891 papers

TitleStatusHype
Pixel Contrastive-Consistent Semi-Supervised Semantic Segmentation—0
Parallel Quasi-concave set optimization: A new frontier that scales without needing submodularity—0
Simple is better: Making Decision Trees faster using random sampling—0
A Simple and Efficient Reconstruction Backbone for Snapshot Compressive ImagingCode1
M-ar-K-Fast Independent Component AnalysisCode0
Seismic wave propagation and inversion with Neural Operators—0
Maximizing Influence with Graph Neural Networks—0
An Extensible Benchmark Suite for Learning to Simulate Physical SystemsCode1
Token Shift Transformer for Video ClassificationCode1
Exact Pareto Optimal Search for Multi-Task Learning and Multi-Criteria Decision-Making—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified