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 1901–1950 of 4891 papers

TitleStatusHype
Feature Normalization Prevents Collapse of Non-contrastive Learning Dynamics—0
Dimensionality Reduction in Sentence Transformer Vector Databases with Fast Fourier Transform—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
Accelerating Coordinate Descent via Active Set Selection for Device Activity Detection for Multi-Cell Massive Random Access—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
Digital Twin-Empowered Voltage Control for Power Systems—0
Automated Tomato Maturity Estimation Using an Optimized Residual Model with Pruning and Quantization Techniques—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
FedPaI: Achieving Extreme Sparsity in Federated Learning via Pruning at Initialization—0
Generalizability of Mixture of Domain-Specific Adapters from the Lens of Signed Weight Directions and its Application to Effective Model Pruning—0
FedSCA: Federated Tuning with Similarity-guided Collaborative Aggregation for Heterogeneous Medical Image Segmentation—0
Generalizable Implicit Neural Representations via Parameterized Latent Dynamics for Baroclinic Ocean Forecasting—0
Fed-ZOE: Communication-Efficient Over-the-Air Federated Learning via Zeroth-Order Estimation—0
Computationally Efficient Safe Control of Linear Systems under Severe Sensor Attacks—0
Computationally efficient spatial rendering of late reverberation in virtual acoustic environments—0
Generalized Nesterov's Acceleration-incorporated Non-negative and Adaptive Latent Factor Analysis—0
Ferroelectric MirrorBit-Integrated Field-Programmable Memory Array for TCAM, Storage, and In-Memory Computing Applications—0
Few-Shot Class-Incremental Learning For Efficient SAR Automatic Target Recognition—0
Digital Twin Data Modelling by Randomized Orthogonal Decomposition and Deep Learning—0
Digital twin-assisted three-dimensional electrical capacitance tomography for multiphase flow imaging—0
Accurate and efficient Simulation of very high-dimensional Neural Mass Models with distributed-delay Connectome Tensors—0
Fighting Fire with Fire (F3): A Training-free and Efficient Visual Adversarial Example Purification Method in LVLMs—0
Computation and Communication Efficient Lightweighting Vertical Federated Learning for Smart Building IoT—0
Applying Incremental Learning in Binary-Addition-Tree Algorithm for Dynamic Binary-State Network Reliability—0
Automated Process Planning for Hybrid Manufacturing—0
Diffusion Models in 3D Vision: A Survey—0
Computation-efficient Virtual Sensing Approach with Multichannel Adjoint Least Mean Square Algorithm—0
Finding Optimal Kernel Size and Dimension in Convolutional Neural Networks An Architecture Optimization Approach—0
Finding path and cycle counting formulae in graphs with Deep Reinforcement Learning—0
Finding Statistically Significant Interactions between Continuous Features—0
Diffusion Models for High-Resolution Solar Forecasts—0
Automated Linear-Time Detection and Quality Assessment of Superpixels in Uncalibrated True- or False-Color RGB Images—0
Alternates, Assemble! Selecting Optimal Alternates for Citizens' Assemblies—0
DiffusionBlend: Learning 3D Image Prior through Position-aware Diffusion Score Blending for 3D Computed Tomography Reconstruction—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified