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 3151–3175 of 4891 papers

TitleStatusHype
Unsupervised Synchrony Discovery in Human Interaction—0
Unveiling Delay Effects in Traffic Forecasting: A Perspective from Spatial-Temporal Delay Differential Equations—0
UnWave-Net: Unrolled Wavelet Network for Compton Tomography Image Reconstruction—0
UOUO: Uncontextualized Uncommon Objects for Measuring Knowledge Horizons of Vision Language Models—0
Uplink Transmission Design for Fluid Antenna-Enabled Multiuser MIMO Systems with Imperfect CSI—0
Upper and Lower Bounds for Distributionally Robust Off-Dynamics Reinforcement Learning—0
Upsample or Upweight? Balanced Training on Heavily Imbalanced Datasets—0
Use of Boosting Algorithms in Household-Level Poverty Measurement: A Machine Learning Approach to Predict and Classify Household Wealth Quintiles in the Philippines—0
Using Convolutional Neural Networks to Detect Compression Algorithms—0
US \& MRI Image Fusion Based on Markerless Skin Registration—0
U-Statistics for Importance-Weighted Variational Inference—0
Utility-Based Control for Computer Vision—0
UVCG: Leveraging Temporal Consistency for Universal Video Protection—0
V2V3D: View-to-View Denoised 3D Reconstruction for Light-Field Microscopy—0
V2V3D: View-to-View Denoised 3D Reconstruction for Light Field Microscopy—0
Value-Agnostic Conversational Semantic Parsing—0
Value-of-Information based Arbitration between Model-based and Model-free Control—0
VAMO: Efficient Large-Scale Nonconvex Optimization via Adaptive Zeroth Order Variance Reduction—0
Vanilla Transformers are Transfer Capability Teachers—0
Variance-Dependent Regret Bounds for Linear Bandits and Reinforcement Learning: Adaptivity and Computational Efficiency—0
Variance Reduced Median-of-Means Estimator for Byzantine-Robust Distributed Inference—0
Variational Approach for Efficient KL Divergence Estimation in Dirichlet Mixture Models—0
Variational Autoencoded Multivariate Spatial Fay-Herriot Models—0
Variational Autoencoders for Efficient Simulation-Based Inference—0
Variational Autoencoding of PDE Inverse Problems—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified