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 3881–3890 of 4891 papers

TitleStatusHype
A Question of Time: Revisiting the Use of Recursive Filtering for Temporal Calibration of Multisensor Systems—0
Pixel super-resolved lensless on-chip sensor with scattering multiplexing—0
Robust Regularization with Adversarial Labelling of Perturbed Samples—0
TransCamP: Graph Transformer for 6-DoF Camera Pose Estimation—0
Federated Learning for Short-term Residential Load Forecasting—0
One4all User Representation for Recommender Systems in E-commerce—0
Revisiting 2D Convolutional Neural Networks for Graph-based Applications—0
Combining Recurrent, Convolutional, and Continuous-time Models with Linear State Space Layers—0
Deep learning of transition probability densities for stochastic asset models with applications in option pricing—0
Statistical Optimality and Computational Efficiency of Nyström Kernel PCA—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified