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 4001–4025 of 4891 papers

TitleStatusHype
Data-Centric Learning Framework for Real-Time Detection of Aiming Beam in Fluorescence Lifetime Imaging Guided Surgery—0
Data Clustering and Visualization with Recursive Goemans-Williamson MaxCut Algorithm—0
Data Collaboration Analysis with Orthonormal Basis Selection and Alignment—0
Data denoising with self consistency, variance maximization, and the Kantorovich dominance—0
Data-driven approaches to inverse problems—0
Data-Driven Approximation of Binary-State Network Reliability Function: Algorithm Selection and Reliability Thresholds for Large-Scale Systems—0
Data-Driven Distributionally Robust Scheduling of Community Integrated Energy Systems with Uncertain Renewable Generations Considering Integrated Demand Response—0
Data-driven HRF estimation for encoding and decoding models—0
Data-Driven Model Discrimination of Switched Nonlinear Systems with Temporal Logic Inference—0
Data-driven Modeling of Linearizable Power Flow for Large-scale Grid Topology Optimization—0
Data-driven operator learning for energy-efficient building control—0
Data-Driven Outage Restoration Time Prediction via Transfer Learning with Cluster Ensembles—0
Data-driven Power Flow Linearization: Simulation—0
Data-driven Power Flow Linearization: Theory—0
Data-driven Power Loss Identification through Physics-Based Thermal Model Backpropagation—0
Data-driven sparse polynomial chaos expansion for models with dependent inputs—0
Data-Driven Surrogate Modeling Techniques to Predict the Effective Contact Area of Rough Surface Contact Problems—0
Data-Driven Threshold Machine: Scan Statistics, Change-Point Detection, and Extreme Bandits—0
Data-Efficient Interactive Multi-Objective Optimization Using ParEGO—0
Data-Enabled Predictive Control for Flexible Spacecraft—0
DB-LLM: Accurate Dual-Binarization for Efficient LLMs—0
DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer—0
DCE: Offline Reinforcement Learning With Double Conservative Estimates—0
DCF-ASN: Coarse-to-fine Real-time Visual Tracking via Discriminative Correlation Filter and Attentional Siamese Network—0
D-CODE: Data Colony Optimization for Dynamic Network Efficiency—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified