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 3651–3660 of 4891 papers

TitleStatusHype
A Survey of Distributed Learning in Cloud, Mobile, and Edge Settings—0
A Survey on Deep Learning Methods for Semantic Image Segmentation in Real-Time—0
A Survey on Graph Condensation—0
A Survey on Kolmogorov-Arnold Network—0
From S4 to Mamba: A Comprehensive Survey on Structured State Space Models—0
A Survey on Computationally Efficient Neural Architecture Search—0
A Survey on the Integration of Machine Learning with Sampling-based Motion Planning—0
A Survey on Vietnamese Document Analysis and Recognition: Challenges and Future Directions—0
A Symbolic and Statistical Learning Framework to Discover Bioprocessing Regulatory Mechanism: Cell Culture Example—0
A Refined Equilibrium Generative Adversarial Network for Retinal Vessel Segmentation—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified