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 3841–3850 of 4891 papers

TitleStatusHype
Data-based stochastic modeling reveals sources of activity bursts in single-cell TGF-β signalingCode0
Dispatch of Virtual Inertia and Damping: Numerical Method with SDP and ADMM—0
Logspace Reducibility From Secret Leakage Planted Clique—0
Optimal Operation of Power Systems with Energy Storage under Uncertainty: A Scenario-based Method with Strategic Sampling—0
Stein Variational Gradient Descent with Multiple Kernel—0
Precision-Weighted Federated Learning—0
Robust Topology Optimization Using Multi-Fidelity Variational Autoencoders—0
Solving Large-Scale Multi-Objective Optimization via Probabilistic Prediction Model—0
Continuous vs. Discrete Optimization of Deep Neural NetworksCode0
Accelerating Spherical k-Means—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified