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

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Showing 351–360 of 4891 papers

TitleStatusHype
Learning based convex approximation for constrained parametric optimization—0
MambaStyle: Efficient StyleGAN Inversion for Real Image Editing with State-Space Models—0
SAND: One-Shot Feature Selection with Additive Noise Distortion—0
Model Predictive Fuzzy Control: A Hierarchical Multi-Agent Control Architecture for Outdoor Search-and-Rescue Robots—0
GNN-enabled Precoding for Massive MIMO LEO Satellite Communications—0
A Symbolic and Statistical Learning Framework to Discover Bioprocessing Regulatory Mechanism: Cell Culture Example—0
Latent Adaptive Planner for Dynamic Manipulation—0
Learning Symbolic Persistent Macro-Actions for POMDP Solving Over Time—0
Comparative Analysis of Lightweight Deep Learning Models for Memory-Constrained Devices—0
Less is More: Efficient Weight Farcasting with 1-Layer Neural Network—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified