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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 2751–2775 of 4891 papers

TitleStatusHype
HyperLISTA-ABT: An Ultra-light Unfolded Network for Accurate Multi-component Differential Tomographic SAR Inversion—0
A parsimonious, computationally efficient machine learning method for spatial regression—0
An Enhanced Low-Resolution Image Recognition Method for Traffic Environments—0
Feature Normalization Prevents Collapse of Non-contrastive Learning Dynamics—0
Improving Facade Parsing with Vision Transformers and Line IntegrationCode1
Partial Transport for Point-Cloud Registration—0
Balancing Computational Efficiency and Forecast Error in Machine Learning-based Time-Series Forecasting: Insights from Live Experiments on Meteorological Nowcasting—0
Advanced Volleyball Stats for All Levels: Automatic Setting Tactic Detection and Classification with a Single CameraCode0
Detach-ROCKET: Sequential feature selection for time series classification with random convolutional kernelsCode1
AsymFormer: Asymmetrical Cross-Modal Representation Learning for Mobile Platform Real-Time RGB-D Semantic SegmentationCode1
Accelerating Machine Learning Algorithms with Adaptive Sampling—0
Tackling Intertwined Data and Device Heterogeneities in Federated Learning with Unlimited StalenessCode0
Nonparametric mixed logit model with market-level parameters estimated from market share data—0
Evidential Deep Learning: Enhancing Predictive Uncertainty Estimation for Earth System Science ApplicationsCode1
Efficient N:M Sparse DNN Training Using Algorithm, Architecture, and Dataflow Co-Design—0
Bridging Sensor Gaps via Attention Gated Tuning for Hyperspectral Image ClassificationCode0
Prompt Tuned Embedding Classification for Multi-Label Industry Sector AllocationCode1
Benchmarking quantized LLaMa-based models on the Brazilian Secondary School Exam—0
A Dynamic Linear Bias Incorporation Scheme for Nonnegative Latent Factor Analysis—0
FRAMU: Attention-based Machine Unlearning using Federated Reinforcement Learning—0
Source-free Active Domain Adaptation for Diabetic Retinopathy Grading Based on Ultra-wide-field Fundus ImageCode0
Posterior sampling algorithms for unsupervised speech enhancement with recurrent variational autoencoder—0
Learning Dynamic MRI Reconstruction with Convolutional Network Assisted Reconstruction Swin Transformer—0
Asynchronous Perception-Action-Communication with Graph Neural Networks—0
An Autonomous Vision-Based Algorithm for Interplanetary Navigation—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified