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 1141–1150 of 4891 papers

TitleStatusHype
A Hybrid Mixture of t-Factor Analyzers for Clustering High-dimensional Data—0
Exploiting inter-agent coupling information for efficient reinforcement learning of cooperative LQR—0
Improving trajectory continuity in drone-based crowd monitoring using a set of minimal-cost techniques and deep discriminative correlation filters—0
Fault Detection and Human Intervention in Vehicle Platooning: A Multi-Model Framework—0
MLICv2: Enhanced Multi-Reference Entropy Modeling for Learned Image Compression—0
Transformer-Empowered Actor-Critic Reinforcement Learning for Sequence-Aware Service Function Chain Partitioning—0
Nonconvex Linear System Identification with Minimal State Representation—0
Outlier-aware Tensor Robust Principal Component Analysis with Self-guided Data Augmentation—0
Appa: Bending Weather Dynamics with Latent Diffusion Models for Global Data Assimilation—0
PODNO: Proper Orthogonal Decomposition Neural Operators—0
Show:102550
← PrevPage 115 of 490Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified