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 2451–2460 of 4891 papers

TitleStatusHype
Curriculum reinforcement learning for quantum architecture search under hardware errors—0
Representation Surgery for Multi-Task Model MergingCode1
Nonlinear subspace clustering by functional link neural networks—0
A Survey on Graph Condensation—0
kNN Algorithm for Conditional Mean and Variance Estimation with Automated Uncertainty Quantification and Variable Selection—0
Scalable Multi-modal Model Predictive Control via Duality-based Interaction PredictionsCode1
A Robust Super-resolution Gridless Imaging Framework for UAV-borne SAR Tomography—0
Unveiling Delay Effects in Traffic Forecasting: A Perspective from Spatial-Temporal Delay Differential Equations—0
Multivariate Probabilistic Time Series Forecasting with Correlated ErrorsCode1
Parallel Spiking Unit for Efficient Training of Spiking Neural Networks—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified