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 2401–2410 of 4891 papers

TitleStatusHype
Bayesian Off-Policy Evaluation and Learning for Large Action Spaces—0
A Self-supervised Pressure Map human keypoint Detection Approch: Optimizing Generalization and Computational Efficiency Across Datasets—0
Global Safe Sequential Learning via Efficient Knowledge TransferCode0
MAPE-PPI: Towards Effective and Efficient Protein-Protein Interaction Prediction via Microenvironment-Aware Protein EmbeddingCode3
Learning Dual-arm Object Rearrangement for Cartesian Robots—0
Improving Building Temperature Forecasting: A Data-driven Approach with System Scenario Clustering—0
Tumor segmentation on whole slide images: training or prompting?—0
EffLoc: Lightweight Vision Transformer for Efficient 6-DOF Camera Relocalization—0
VOOM: Robust Visual Object Odometry and Mapping using Hierarchical LandmarksCode2
FAST: An Optimization Framework for Fast Additive Segmentation in Transparent ML—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified