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

Showing 11911200 of 4891 papers

TitleStatusHype
Alternating Local Enumeration (TnALE): Solving Tensor Network Structure Search with Fewer EvaluationsCode0
Gaussian Ensemble Belief Propagation for Efficient Inference in High-Dimensional SystemsCode0
GCNv2: Efficient Correspondence Prediction for Real-Time SLAMCode0
Generalized Population-Based Training for Hyperparameter Optimization in Reinforcement LearningCode0
GAMMA: A General Agent Motion Model for Autonomous DrivingCode0
GARG-AML against Smurfing: A Scalable and Interpretable Graph-Based Framework for Anti-Money LaunderingCode0
Federated Hybrid Model Pruning through Loss Landscape ExplorationCode0
Scaling Video Analytics on Constrained Edge NodesCode0
Gated Fusion Network for Joint Image Deblurring and Super-ResolutionCode0
Studying K-FAC Heuristics by Viewing Adam through a Second-Order LensCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05Unverified