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 3351–3360 of 4891 papers

TitleStatusHype
Sliced-Wasserstein on Symmetric Positive Definite Matrices for M/EEG SignalsCode0
A robust method for reliability updating with equality information using sequential adaptive importance sampling—0
Agnostic PAC Learning of k-juntas Using L2-Polynomial Regression—0
Radio astronomical images object detection and segmentation: A benchmark on deep learning methods—0
Fast Latent Factor Analysis via a Fuzzy PID-Incorporated Stochastic Gradient Descent Algorithm—0
TMHOI: Translational Model for Human-Object Interaction Detection—0
Scatter-based common spatial patterns -- a unified spatial filtering framework—0
Maximizing Spatio-Temporal Entropy of Deep 3D CNNs for Efficient Video Recognition—0
Iterative Approximate Cross-ValidationCode0
CAMEL: Curvature-Augmented Manifold Embedding and Learning—0
Show:102550
← PrevPage 336 of 490Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified