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 3876–3900 of 4891 papers

TitleStatusHype
Combining Retrospective Approximation with Importance Sampling for Optimising Conditional Value at Risk—0
Combining the band-limited parameterization and Semi-Lagrangian Runge--Kutta integration for efficient PDE-constrained LDDMM—0
Communication-Efficient Decentralized Federated Learning via One-Bit Compressive Sensing—0
Communication-Efficient Distributed Statistical Inference—0
Communication Optimization for Decentralized Learning atop Bandwidth-limited Edge Networks—0
Community detection by spectral methods in multi-layer networks—0
Compact and Efficient Encodings for Planning in Factored State and Action Spaces with Learned Binarized Neural Network Transition Models—0
Comparative Analysis of Advanced AI-based Object Detection Models for Pavement Marking Quality Assessment during Daytime—0
Comparative Analysis of CNN and Transformer Architectures with Heart Cycle Normalization for Automated Phonocardiogram Classification—0
Comparative Analysis of Lightweight Deep Learning Models for Memory-Constrained Devices—0
Comparative Analysis of Multi-Agent Reinforcement Learning Policies for Crop Planning Decision Support—0
Comparative Analysis of Radiomic Features and Gene Expression Profiles in Histopathology Data Using Graph Neural Networks—0
Comparative Analysis of Vision Transformers and Traditional Deep Learning Approaches for Automated Pneumonia Detection in Chest X-Rays—0
Comparative Analysis of XGBoost and Minirocket Algortihms for Human Activity Recognition—0
Comparative Study of MPPT and Parameter Estimation of PV cells—0
Comparative Study of Neural Network Methods for Solving Topological Solitons—0
Comparing hundreds of machine learning classifiers and discrete choice models in predicting travel behavior: an empirical benchmark—0
Complementary Advantages: Exploiting Cross-Field Frequency Correlation for NIR-Assisted Image Denoising—0
Complexity-Driven CNN Compression for Resource-constrained Edge AI—0
Composable Cross-prompt Essay Scoring by Merging Models—0
Composing MPC with LQR and Neural Network for Amortized Efficiency and Stable Control—0
Composite Event Recognition for Maritime Monitoring—0
Composite Gaussian Processes Flows for Learning Discontinuous Multimodal Policies—0
Composite Marginal Likelihood Methods for Random Utility Models—0
Compositionally-Warped Gaussian Processes—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified