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 1861–1870 of 4891 papers

TitleStatusHype
Fast Learning in Quantitative Finance with Extreme Learning Machine—0
A novel active learning-based Gaussian process metamodelling strategy for estimating the full probability distribution in forward UQ analysis—0
Collaborative Deterministic-Probabilistic Forecasting for Real-World Spatiotemporal Systems—0
A Deep Unrolling Model with Hybrid Optimization Structure for Hyperspectral Image Deconvolution—0
Fast Matching by 2 Lines of Code for Large Scale Face Recognition Systems—0
Fast Maximum Likelihood Estimation and Supervised Classification for the Beta-Liouville Multinomial—0
Fall Detection for Industrial Setups Using YOLOv8 Variants—0
FakeWatch ElectionShield: A Benchmarking Framework to Detect Fake News for Credible US Elections—0
Fast Nonconvex SDP Solvers for Large-scale Power System State Estimation—0
FakeWatch: A Framework for Detecting Fake News to Ensure Credible Elections—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified