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 4126–4150 of 4891 papers

TitleStatusHype
Decentralized and Lifelong-Adaptive Multi-Agent Collaborative LearningCode0
Active ML for 6G: Towards Efficient Data Generation, Acquisition, and AnnotationCode0
Interweaving Insights: High-Order Feature Interaction for Fine-Grained Visual RecognitionCode0
Introducing a microstructure-embedded autoencoder approach for reconstructing high-resolution solution field data from a reduced parametric spaceCode0
Online Human Action Detection using Joint Classification-Regression Recurrent Neural NetworksCode0
Bisimulation metric for Model Predictive ControlCode0
A Spatially-Aware Multiple Instance Learning Framework for Digital PathologyCode0
Revisiting DeepFool: generalization and improvementCode0
SpatioTemporal Feature Integration and Model Fusion for Full Reference Video Quality AssessmentCode0
Online Physics-Informed Dynamic Mode Decomposition: Theory and ApplicationsCode0
Online Tensor Methods for Learning Latent Variable ModelsCode0
The Deep Promotion Time Cure ModelCode0
The demodulated band transformCode0
Hyperbolic Procrustes Analysis Using Riemannian GeometryCode0
BIP: Boost Invariant Polynomials for Efficient Jet TaggingCode0
Debiasing Evidence Approximations: On Importance-weighted Autoencoders and Jackknife Variational InferenceCode0
I-SplitEE: Image classification in Split Computing DNNs with Early ExitsCode0
SPDNet: Seasonal-Periodic Decomposition Network for Advanced Residential Demand ForecastingCode0
DeBaCl: A Python Package for Interactive DEnsity-BAsed CLusteringCode0
DCR: Quantifying Data Contamination in LLMs EvaluationCode0
Iterative Approximate Cross-ValidationCode0
Iterative Distributed Multinomial RegressionCode0
Iterative Distance-Aware Similarity Matrix Convolution with Mutual-Supervised Point Elimination for Efficient Point Cloud RegistrationCode0
Iterative Projection and Matching: Finding Structure-preserving Representatives and Its Application to Computer VisionCode0
Iterative Semi-Supervised Learning for Abdominal Organs and Tumor SegmentationCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified