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 1841–1850 of 4891 papers

TitleStatusHype
Federated Learning for Coronary Artery Plaque Detection in Atherosclerosis Using IVUS Imaging: A Multi-Hospital Collaboration—0
Enhancing Diffusion Models for High-Quality Image Generation—0
Energy and polarization based on-line interference mitigation in radio interferometryCode0
Surrogate-assisted multi-objective design of complex multibody systems—0
From Point to probabilistic gradient boosting for claim frequency and severity prediction—0
Robust PCA Based on Adaptive Weighted Least Squares and Low-Rank Matrix Factorization—0
Subspace Langevin Monte Carlo—0
PreMixer: MLP-Based Pre-training Enhanced MLP-Mixers for Large-scale Traffic Forecasting—0
Rare Event Detection in Imbalanced Multi-Class Datasets Using an Optimal MIP-Based Ensemble Weighting ApproachCode0
E-CAR: Efficient Continuous Autoregressive Image Generation via Multistage Modeling—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified