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 2881–2890 of 4891 papers

TitleStatusHype
Image edge enhancement for effective image classification—0
Data-Efficient Interactive Multi-Objective Optimization Using ParEGO—0
A Physics-informed machine learning model for time-dependent wave runup prediction—0
Plug-in for visualizing 3D tool tracking from videos of Minimally Invasive Surgeries—0
Maximum-Entropy Adversarial Audio Augmentation for Keyword Spotting—0
A Lightweight Feature Fusion Architecture For Resource-Constrained Crowd Counting—0
Reliability Analysis of Complex Systems using Subset Simulations with Hamiltonian Neural Networks—0
Feature Network Methods in Machine Learning and Applications—0
DiffSHEG: A Diffusion-Based Approach for Real-Time Speech-driven Holistic 3D Expression and Gesture Generation—0
FlightLLM: Efficient Large Language Model Inference with a Complete Mapping Flow on FPGAs—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified