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

Showing 41264150 of 4891 papers

TitleStatusHype
Speech to Text Adaptation: Towards an Efficient Cross-Modal Distillation0
Convolutional Neural Network for emotion recognition to assist psychiatrists and psychologists during the COVID-19 pandemic: experts opinion0
Visual Perception Model for Rapid and Adaptive Low-light Image Enhancement0
Adaptive Transformers for Learning Multimodal RepresentationsCode1
Walking with Perception: Efficient Random Walk Sampling via Common Neighbor Awareness0
Accelerating Deep Neuroevolution on Distributed FPGAs for Reinforcement Learning Problems0
Dynamic Shrinkage Priors for Large Time-varying Parameter Regressions using Scalable Markov Chain Monte Carlo Methods0
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 RKHSs0
Efficient and Information-Preserving Future Frame Prediction and BeyondCode1
Multilingual Joint Fine-tuning of Transformer models for identifying Trolling, Aggression and Cyberbullying at TRAC 2020Code0
The 4th AI City Challenge0
EfficientPose: Scalable single-person pose estimationCode1
Self-Organized Operational Neural Networks with Generative NeuronsCode1
Automatic exposure selection and fusion for high-dynamic-range photography via smartphones0
MiniSeg: An Extremely Minimum Network for Efficient COVID-19 SegmentationCode1
Predicting Online Item-choice Behavior: A Shape-restricted Regression Perspective0
Biophysically detailed mathematical models of multiscale cardiac active mechanicsCode0
Scaling Bayesian inference of mixed multinomial logit models to very large datasets0
Encoder blind combinatorial compressed sensing0
Cortical surface registration using unsupervised learningCode0
Towards Reusable Network Components by Learning Compatible Representations0
Direct loss minimization algorithms for sparse Gaussian processesCode0
Radon cumulative distribution transform subspace modeling for image classificationCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05Unverified