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 4391–4400 of 4891 papers

TitleStatusHype
Composite Event Recognition for Maritime Monitoring—0
A DenseNet Based Approach for Multi-Frame In-Loop Filter in HEVC—0
Safety Verification and Robustness Analysis of Neural Networks via Quadratic Constraints and Semidefinite ProgrammingCode0
GCNv2: Efficient Correspondence Prediction for Real-Time SLAMCode0
Lipschitz Adaptivity with Multiple Learning Rates in Online Learning—0
Nonlinear Approximation via Compositions—0
SSA-CNN: Semantic Self-Attention CNN for Pedestrian Detection—0
Appearance-based Gesture recognition in the compressed domain—0
Significance Tests for Neural NetworksCode0
Fast Task-Aware Architecture Inference—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified