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

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Showing 3141–3150 of 4891 papers

TitleStatusHype
Fast and Blind Speech Copy-Move Detection and Localization in Noise—0
A model-free feature selection technique of feature screening and random forest based recursive feature elimination—0
The Framework Tax: Disparities Between Inference Efficiency in NLP Research and DeploymentCode0
Transient Hemodynamics Prediction Using an Efficient Octree-Based Deep Learning Model—0
Density-Softmax: Efficient Test-time Model for Uncertainty Estimation and Robustness under Distribution ShiftsCode0
Towards Fairer and More Efficient Federated Learning via Multidimensional Personalized Edge Models—0
Learning to Select Pivotal Samples for Meta Re-weightingCode0
3D Human Pose and Shape Estimation via HybrIK-TransformerCode1
On the Convergence of Modified Policy Iteration in Risk Sensitive Exponential Cost Markov Decision Processes—0
Single Cells Are Spatial Tokens: Transformers for Spatial Transcriptomic Data ImputationCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified