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 1551–1575 of 4891 papers

TitleStatusHype
Curbing Task Interference using Representation Similarity-Guided Multi-Task Feature SharingCode0
Federated Learning for Time-Series Healthcare Sensing with Incomplete ModalitiesCode0
Gated Texture CNN for Efficient and Configurable Image DenoisingCode0
BlazeNeo: Blazing fast polyp segmentation and neoplasm detectionCode0
Fast Fair Regression via Efficient Approximations of Mutual InformationCode0
FasterVideo: Efficient Online Joint Object Detection And TrackingCode0
CrowdSplat: Exploring Gaussian Splatting For Crowd RenderingCode0
Fast Counting in Machine Learning ApplicationsCode0
Efficient Neural Network Approaches for Conditional Optimal Transport with Applications in Bayesian InferenceCode0
Fast Decision Boundary based Out-of-Distribution DetectorCode0
Fast CapsNet for Lung Cancer ScreeningCode0
Fast Discrete Distribution Clustering Using Wasserstein Barycenter with Sparse SupportCode0
Fast and Reliable Evaluation of Adversarial Robustness with Minimum-Margin AttackCode0
Cross Language Soccer Framework: An Open Source Framework for the RoboCup 2D Soccer SimulationCode0
Agentic AI for Behavior-Driven Development Testing Using Large Language ModelsCode0
Accelerated Structured Alternating Projections for Robust Spectrally Sparse Signal RecoveryCode0
Cross-D Conv: Cross-Dimensional Transferable Knowledge Base via Fourier Shifting OperationCode0
Cross-Context Backdoor Attacks against Graph Prompt LearningCode0
Fast Incremental von Neumann Graph Entropy Computation: Theory, Algorithm, and ApplicationsCode0
Faithful Group Shapley ValueCode0
Falcon: Fair Active Learning using Multi-armed BanditsCode0
Criteria Tell You More than Ratings: Criteria Preference-Aware Light Graph Convolution for Effective Multi-Criteria RecommendationCode0
Criteria-Aware Graph Filtering: Extremely Fast Yet Accurate Multi-Criteria RecommendationCode0
Efficient Quantification and Representation of Aggregate Flexibility in Electric VehiclesCode0
A Runtime-Adaptive Transformer Neural Network Accelerator on FPGAsCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified