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 4151–4175 of 4891 papers

TitleStatusHype
Combining the band-limited parameterization and Semi-Lagrangian Runge--Kutta integration for efficient PDE-constrained LDDMM—0
GAP++: Learning to generate target-conditioned adversarial examples—0
Neural Network Activation Quantization with Bitwise Information BottlenecksCode0
Smart Forgetting for Safe Online Learning with Gaussian Processes—0
Learning Mixtures of Random Utility Models with Features from Incomplete Preferences—0
Look Locally Infer Globally: A Generalizable Face Anti-Spoofing Approach—0
Anomaly Detection with Tensor Networks—0
Quantifying the Uncertainty in Model Parameters Using Gaussian Process-Based Markov Chain Monte Carlo: An Application to Cardiac Electrophysiological Models—0
Learning to Generate 3D Training Data Through Hybrid Gradient—0
On scenario construction for stochastic shortest path problems in real road networks—0
Instability, Computational Efficiency and Statistical Accuracy—0
Beyond the Mean-Field: Structured Deep Gaussian Processes Improve the Predictive UncertaintiesCode0
Optimal Distributed Subsampling for Maximum Quasi-Likelihood Estimators with Massive Data—0
MOTS: Multiple Object Tracking for General Categories Based On Few-Shot Method—0
An Efficient Machine-Learning Approach for PDF Tabulation in Turbulent Combustion Closure—0
Speech to Text Adaptation: Towards an Efficient Cross-Modal Distillation—0
Convolutional Neural Network for emotion recognition to assist psychiatrists and psychologists during the COVID-19 pandemic: experts opinion—0
Visual Perception Model for Rapid and Adaptive Low-light Image Enhancement—0
Walking with Perception: Efficient Random Walk Sampling via Common Neighbor Awareness—0
Accelerating Deep Neuroevolution on Distributed FPGAs for Reinforcement Learning Problems—0
Dynamic Shrinkage Priors for Large Time-varying Parameter Regressions using Scalable Markov Chain Monte Carlo Methods—0
The scalable Birth-Death MCMC Algorithm for Mixed Graphical Model Learning with Application to Genomic Data IntegrationCode0
Development of a skateboarding trick classifier using accelerometry and machine learningCode0
Mathematical foundations of stable RKHSs—0
Multilingual Joint Fine-tuning of Transformer models for identifying Trolling, Aggression and Cyberbullying at TRAC 2020Code0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified