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 3571–3580 of 4891 papers

TitleStatusHype
Robust optimal well control using an adaptive multi-grid reinforcement learning frameworkCode0
Careful Seeding for k-Medois Clustering with Incremental k-Means++ Initialization—0
Data-driven synchronization-avoiding algorithms in the explicit distributed structural analysis of soft tissueCode0
Location reference recognition from texts: A survey and comparison—0
Mathematical Foundations of Graph-Based Bayesian Semi-Supervised Learning—0
Asynchronous Decentralized Bayesian Optimization for Large Scale Hyperparameter Optimization—0
On the Computational Efficiency of Adaptive and Dynamic Regret Minimization—0
LiteCON: An All-Photonic Neuromorphic Accelerator for Energy-efficient Deep Learning (Preprint)—0
On the Calculation of the Variance of Algebraic Variables in Power System Dynamic Models with Stochastic Processes—0
Two-Stage Neural Contextual Bandits for Personalised News RecommendationCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified