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 1901–1925 of 4891 papers

TitleStatusHype
Feature Normalization Prevents Collapse of Non-contrastive Learning Dynamics—0
Accelerating Coordinate Descent via Active Set Selection for Device Activity Detection for Multi-Cell Massive Random Access—0
Feature Selection via GANs (GANFS): Enhancing Machine Learning Models for DDoS Mitigation—0
Compressing Recurrent Neural Networks for FPGA-accelerated Implementation in Fluorescence Lifetime Imaging—0
Feature-Specific Coefficients of Determination in Tree Ensembles—0
Feature subset selection for kernel SVM classification via mixed-integer optimization—0
FedAPA: Server-side Gradient-Based Adaptive Personalized Aggregation for Federated Learning on Heterogeneous Data—0
FedBlockHealth: A Synergistic Approach to Privacy and Security in IoT-Enabled Healthcare through Federated Learning and Blockchain—0
FedCanon: Non-Convex Composite Federated Learning with Efficient Proximal Operation on Heterogeneous Data—0
Digital Twin-Empowered Voltage Control for Power Systems—0
Federated Fine-Tuning of LLMs on the Very Edge: The Good, the Bad, the Ugly—0
Federated Instruction Tuning of LLMs with Domain Coverage Augmentation—0
Federated K-Means Clustering via Dual Decomposition-based Distributed Optimization—0
Federated Learning for Coronary Artery Plaque Detection in Atherosclerosis Using IVUS Imaging: A Multi-Hospital Collaboration—0
Federated Learning for Efficient Condition Monitoring and Anomaly Detection in Industrial Cyber-Physical Systems—0
Federated Learning for Medical Image Classification: A Comprehensive Benchmark—0
Federated Learning for Short-term Residential Load Forecasting—0
Federated Learning for Sparse Principal Component Analysis—0
Automated Tomato Maturity Estimation Using an Optimized Residual Model with Pruning and Quantization Techniques—0
GARLIC: LLM-Guided Dynamic Progress Control with Hierarchical Weighted Graph for Long Document QA—0
Computational Explorations in Biomedicine: Unraveling Molecular Dynamics for Cancer, Drug Delivery, and Biomolecular Insights using LAMMPS Simulations—0
Applications of Knowledge Distillation in Remote Sensing: A Survey—0
Federated Smoothing ADMM for Localization—0
FedMentalCare: Towards Privacy-Preserving Fine-Tuned LLMs to Analyze Mental Health Status Using Federated Learning Framework—0
GAS: Generative Auto-bidding with Post-training Search—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified