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 3671–3680 of 4891 papers

TitleStatusHype
Efficient Token Mixing for Transformers via Adaptive Fourier Neural Operators—0
Deep neural networks with controlled variable selection for the identification of putative causal genetic variantsCode0
Confusion-based rank similarity filters for computationally-efficient machine learning on high dimensional dataCode0
An Improved Frequent Directions Algorithm for Low-Rank Approximation via Block Krylov Iteration—0
Fast Density Estimation for Density-based Clustering Methods—0
Formulations and Approximations of the Branch Flow Model for Mesh Power Networks—0
An Efficient and Scalable Collection of Fly-inspired Voting Units for Visual Place Recognition in Changing Environments—0
Improved optimization strategies for deep Multi-Task Networks—0
Stochastic MPC with Multi-modal Predictions for Traffic Intersections—0
Fast TreeSHAP: Accelerating SHAP Value Computation for TreesCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified