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 4651–4675 of 4891 papers

TitleStatusHype
Modelling Competitive Sports: Bradley-Terry-Élő Models for Supervised and On-Line Learning of Paired Competition Outcomes—0
Operationalizing Declarative and Procedural Knowledge: a Benchmark on Logic Programming Petri Nets (LPPNs)—0
A graph cut approach to 3D tree delineation, using integrated airborne LiDAR and hyperspectral imagery—0
A Spatial Interpolation Framework for Efficient Valuation of Large Portfolios of Variable Annuities—0
Automated Linear-Time Detection and Quality Assessment of Superpixels in Uncalibrated True- or False-Color RGB Images—0
A Framework for Wasserstein-1-Type Metrics—0
Dynamic Deep Neural Networks: Optimizing Accuracy-Efficiency Trade-offs by Selective Execution—0
Two-Bit Networks for Deep Learning on Resource-Constrained Embedded Devices—0
Superpixel Segmentation Using Gaussian Mixture ModelCode0
Spatially Adaptive Computation Time for Residual NetworksCode0
Robust Low-Complexity Randomized Methods for Locating Outliers in Large Matrices—0
Understanding and Optimizing the Performance of Distributed Machine Learning Applications on Apache Spark—0
Structured Aspect Extraction—0
Efficient and Robust Spiking Neural Circuit for Navigation Inspired by Echolocating Bats—0
Error Analysis of Generalized Nyström Kernel Regression—0
Minimax Optimal Alternating Minimization for Kernel Nonparametric Tensor Learning—0
Improving Variational Auto-Encoders using Householder FlowCode0
Input Switched Affine Networks: An RNN Architecture Designed for Interpretability—0
Dense Prediction on Sequences with Time-Dilated Convolutions for Speech Recognition—0
The Recycling Gibbs Sampler for Efficient Learning—0
Graph Learning from Data under Structural and Laplacian ConstraintsCode0
Dis-S2V: Discourse Informed Sen2VecCode0
Fast and Accurate Surface Normal Integration on Non-Rectangular Domains—0
Data-Driven Threshold Machine: Scan Statistics, Change-Point Detection, and Extreme Bandits—0
Numerical Inversion of SRNF Maps for Elastic Shape Analysis of Genus-Zero Surfaces—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified