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 1131–1140 of 4891 papers

TitleStatusHype
Supervised Dimensionality Reduction for Big DataCode0
Generative Archimedean CopulasCode0
A Multi-Document Coverage Reward for RELAXed Multi-Document SummarizationCode0
Generalized Adaptive Transfer Network: Enhancing Transfer Learning in Reinforcement Learning Across DomainsCode0
GCSAM: Gradient Centralized Sharpness Aware MinimizationCode0
Gaussian Max-Value Entropy Search for Multi-Agent Bayesian OptimizationCode0
Bayesian Neural Networks for Genetic Association Studies of Complex DiseaseCode0
GCNv2: Efficient Correspondence Prediction for Real-Time SLAMCode0
Generalized Population-Based Training for Hyperparameter Optimization in Reinforcement LearningCode0
Gated Fusion Network for Joint Image Deblurring and Super-ResolutionCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified