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 1471–1480 of 4891 papers

TitleStatusHype
Features extraction and reduction techniques with optimized SVM for Persian/Arabic handwritten digits recognitionCode0
Data-driven reduced-order modelling for blood flow simulations with geometry-informed snapshotsCode0
Federated Learning with Reservoir State Analysis for Time Series Anomaly DetectionCode0
Efficient 3D Fully Convolutional Networks for Pulmonary Lobe Segmentation in CT ImagesCode0
Few-Shot Image-to-Semantics Translation for Policy Transfer in Reinforcement LearningCode0
First Exit Time Analysis of Stochastic Gradient Descent Under Heavy-Tailed Gradient NoiseCode0
Flow Annealed Importance Sampling Bootstrap meets Differentiable Particle PhysicsCode0
Assessing Human Editing Effort on LLM-Generated Texts via Compression-Based Edit DistanceCode0
FDAPT: Federated Domain-adaptive Pre-training for Language ModelsCode0
Fast Single Image Dehazing via Multilevel Wavelet Transform based OptimizationCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified