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 3541–3550 of 4891 papers

TitleStatusHype
An FPGA-Based Accelerator Enabling Efficient Support for CNNs with Arbitrary Kernel Sizes—0
Anharmonic Raman spectra simulation of crystals from deep neural networks—0
An improved chromosome formulation for genetic algorithms applied to variable selection with the inclusion of interaction terms—0
An Improved Finite Element Modeling Method for Triply Periodic Minimal Surface Structures Based on Element Size and Minimum Jacobian—0
An Improved Frequent Directions Algorithm for Low-Rank Approximation via Block Krylov Iteration—0
An inexact Newton-Krylov algorithm for constrained diffeomorphic image registration—0
An Initial Seed Selection Algorithm for K-means Clustering of Georeferenced Data to Improve Replicability of Cluster Assignments for Mapping Application—0
An Innovative Networks in Federated Learning—0
An Integer Clustering Approach for Modeling Large-Scale EV Fleets with Guaranteed Performance—0
An Integer Polynomial Programming Based Framework for Lifted MAP Inference—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified