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 1426–1450 of 4891 papers

TitleStatusHype
Improving Hyper-Relational Knowledge Graph CompletionCode0
A Survey on Large-scale Machine LearningCode0
First Exit Time Analysis of Stochastic Gradient Descent Under Heavy-Tailed Gradient NoiseCode0
Decomposing the Time Series Forecasting Pipeline: A Modular Approach for Time Series Representation, Information Extraction, and ProjectionCode0
A Cascaded Dilated Convolution Approach for Mpox Lesion ClassificationCode0
Decomposing and Fusing Intra- and Inter-Sensor Spatio-Temporal Signal for Multi-Sensor Wearable Human Activity RecognitionCode0
DecomCAM: Advancing Beyond Saliency Maps through Decomposition and IntegrationCode0
FinNet: Solving Time-Independent Differential Equations with Finite Difference Neural NetworkCode0
Dynamics-aware Adversarial Attack of Adaptive Neural NetworksCode0
An algorithm for two-player repeated games with imperfect public monitoringCode0
Decentralized and Lifelong-Adaptive Multi-Agent Collaborative LearningCode0
Debiasing Evidence Approximations: On Importance-weighted Autoencoders and Jackknife Variational InferenceCode0
Finding Influential Training Samples for Gradient Boosted Decision TreesCode0
DeBaCl: A Python Package for Interactive DEnsity-BAsed CLusteringCode0
DCR: Quantifying Data Contamination in LLMs EvaluationCode0
Action Recognition Using Temporal Shift Module and Ensemble LearningCode0
Finite-Time Frequentist Regret Bounds of Multi-Agent Thompson Sampling on Sparse HypergraphsCode0
Feed-Forward Optimization With Delayed Feedback for Neural NetworksCode0
Few-Shot Image-to-Semantics Translation for Policy Transfer in Reinforcement LearningCode0
Feedback Gradient Descent: Efficient and Stable Optimization with Orthogonality for DNNsCode0
FGP: Feature-Gradient-Prune for Efficient Convolutional Layer PruningCode0
Federated Learning for Time-Series Healthcare Sensing with Incomplete ModalitiesCode0
DBgDel: Database-Enhanced Gene Deletion Framework for Growth-Coupled Production in Genome-Scale Metabolic ModelsCode0
Federated Learning with Reservoir State Analysis for Time Series Anomaly DetectionCode0
Data-to-Model Distillation: Data-Efficient Learning FrameworkCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified