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 3681–3690 of 4891 papers

TitleStatusHype
A Robust Multimodal Remote Sensing Image Registration Method and System Using Steerable Filters with First- and Second-order Gradients—0
Residual Bootstrap Exploration for Stochastic Linear Bandit—0
CD-ROM: Complemented Deep-Reduced Order Model—0
HoneyModels: Machine Learning Honeypots—0
FinNet: Solving Time-Independent Differential Equations with Finite Difference Neural NetworkCode0
GRAPHSHAP: Explaining Identity-Aware Graph Classifiers Through the Language of Motifs—0
Fast Inverter Control by Learning the OPF Mapping using Sensitivity-Informed Gaussian Processes—0
Tightly Coupled Learning Strategy for Weakly Supervised Hierarchical Place Recognition—0
Efficient Kernel UCB for Contextual BanditsCode0
Scale-free Unconstrained Online Learning for Curved Losses—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified