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 3191–3200 of 4891 papers

TitleStatusHype
Toward Efficient Automated Feature Engineering—0
Learning k-Level Structured Sparse Neural Networks Using Group Envelope Regularization—0
SuperGF: Unifying Local and Global Features for Visual Localization—0
A Survey of Mix-based Data Augmentation: Taxonomy, Methods, Applications, and ExplainabilityCode1
Fast FullSubNet: Accelerate Full-band and Sub-band Fusion Model for Single-channel Speech EnhancementCode2
Efficient Long Sequence Modeling via State Space Augmented TransformerCode1
Joint Delay-Phase Precoding Under True-Time Delay Constraints in Wideband Sub-THz Hybrid Massive MIMO Systems—0
Single Cell Training on Architecture Search for Image Denoising—0
Tool flank wear prediction using high-frequency machine data from industrial edge device—0
Rodin: A Generative Model for Sculpting 3D Digital Avatars Using Diffusion—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified