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 3021–3030 of 4891 papers

TitleStatusHype
Crowd-Certain: Label Aggregation in Crowdsourced and Ensemble Learning Classification—0
Efficient Neural Network Approaches for Conditional Optimal Transport with Applications in Bayesian InferenceCode0
Robust and Actively Secure Serverless Collaborative Learning—0
Stochastic Gradient Sampling for Enhancing Neural Networks Training—0
Numerical Derivative-based Flexible Integration Algorithm for Power Electronic Systems Simulation Considering Nonlinear Components—0
Online Two-stage Thermal History Prediction Method for Metal Additive Manufacturing of Thin Walls—0
Variator: Accelerating Pre-trained Models with Plug-and-Play Compression ModulesCode0
Nested Control Co-design of a Spar Buoy Horizontal-axis Floating Offshore Wind Turbine—0
Efficient Cross-Task Prompt Tuning for Few-Shot Conversational Emotion Recognition—0
Scrap Your Schedules with PopDescent—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified