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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 3981–3990 of 4891 papers

TitleStatusHype
Federated Bayesian Optimization via Thompson SamplingCode1
Efficient and Compact Convolutional Neural Network Architectures for Non-temporal Real-time Fire DetectionCode1
Multi-Agent Motion Planning using Deep Learning for Space Applications—0
CIMON: Towards High-quality Hash Codes—0
Decomposing non-stationary signals with time-varying wave-shape functionsCode1
Rapid Robust Principal Component Analysis: CUR Accelerated Inexact Low Rank EstimationCode0
Graph Deep Factors for Forecasting—0
Sample and Computationally Efficient Stochastic Kriging in High Dimensions—0
How important are faces for person re-identification?—0
Correlation Filters for Unmanned Aerial Vehicle-Based Aerial Tracking: A Review and Experimental EvaluationCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified