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 1221–1230 of 4891 papers

TitleStatusHype
ADAGIO: Fast Data-aware Near-Isometric Linear EmbeddingsCode0
GCSAM: Gradient Centralized Sharpness Aware MinimizationCode0
Generative Archimedean CopulasCode0
GARG-AML against Smurfing: A Scalable and Interpretable Graph-Based Framework for Anti-Money LaunderingCode0
AttriReBoost: A Gradient-Free Propagation Optimization Method for Cold Start Mitigation in Attribute Missing GraphsCode0
Gated Fusion Network for Joint Image Deblurring and Super-ResolutionCode0
Accelerated sparse Kernel Spectral Clustering for large scale data clustering problemsCode0
Functional Autoencoder for Smoothing and Representation LearningCode0
GAMMA: A General Agent Motion Model for Autonomous DrivingCode0
Gated Texture CNN for Efficient and Configurable Image DenoisingCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified