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 3811–3820 of 4891 papers

TitleStatusHype
LOF: Structure-Aware Line Tracking based on Optical Flow—0
Deep Learning based Model-free Robust Load Restoration to Enhance Bulk System Resilience with Wind Power Penetration—0
Gaussian Moments as Physically Inspired Molecular Descriptors for Accurate and Scalable Machine Learning Potentials—0
Towards a variational Jordan-Lee-Preskill quantum algorithm—0
Adaptive Few-Shot Learning PoC Ultrasound COVID-19 Diagnostic System—0
Robust Predictable Control—0
Near-Field Millimeter-Wave Imaging via Arrays in the Shape of Polyline—0
Efficient Action Recognition Using Confidence Distillation—0
Cross-token Modeling with Conditional Computation—0
GTG-Shapley: Efficient and Accurate Participant Contribution Evaluation in Federated LearningCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified