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 4181–4190 of 4891 papers

TitleStatusHype
Encoder blind combinatorial compressed sensing—0
Cortical surface registration using unsupervised learningCode0
Towards Reusable Network Components by Learning Compatible Representations—0
Direct loss minimization algorithms for sparse Gaussian processesCode0
Radon cumulative distribution transform subspace modeling for image classificationCode0
Efficient Scale Estimation Methods using Lightweight Deep Convolutional Neural Networks for Visual Tracking—0
Genetic Algorithmic Parameter Optimisation of a Recurrent Spiking Neural Network Model—0
Coping With Simulators That Don't Always ReturnCode0
Multi-target regression via output space quantization—0
Statistically Guided Divide-and-Conquer for Sparse Factorization of Large Matrix—0
Show:102550
← PrevPage 419 of 490Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified