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 40264050 of 4891 papers

TitleStatusHype
Efficient Folded Attention for 3D Medical Image Reconstruction and Segmentation0
YOLObile: Real-Time Object Detection on Mobile Devices via Compression-Compilation Co-DesignCode1
Low-Rank Training of Deep Neural Networks for Emerging Memory Technology0
Isotonic regression with unknown permutations: Statistics, computation, and adaptation0
Efficiency in Real-time Webcam Gaze Tracking0
Distance Encoding: Design Provably More Powerful Neural Networks for Graph Representation LearningCode1
Is the space complexity of planted clique recovery the same as that of detection?0
Locally induced Gaussian processes for large-scale simulation experiments0
ETC-NLG: End-to-end Topic-Conditioned Natural Language GenerationCode0
Joint Design of RF and gradient waveforms via auto-differentiation for 3D tailored excitation in MRICode1
Neural Bridge Sampling for Evaluating Safety-Critical Autonomous Systems0
An Unsupervised Approach to Ultrasound Elastography with End-to-end Strain Regularisation0
Fuzzy SLIC: Fuzzy Simple Linear Iterative Clustering0
Adversarial Imitation Learning via Random Search0
Doubly Stochastic Variational Inference for Neural Processes with Hierarchical Latent Variables0
Nonparametric Conditional Density Estimation In A Deep Learning Framework For Short-Term Forecasting0
Principal Ellipsoid Analysis (PEA): Efficient non-linear dimension reduction & clustering0
Intelligence plays dice: Stochasticity is essential for machine learning0
Revisiting Temporal Modeling for Video Super-resolutionCode1
DensE: An Enhanced Non-commutative Representation for Knowledge Graph Embedding with Adaptive Semantic HierarchyCode0
A Survey on Large-scale Machine LearningCode0
DIET-SNN: Direct Input Encoding With Leakage and Threshold Optimization in Deep Spiking Neural Networks0
Improving Multispectral Pedestrian Detection by Addressing Modality Imbalance ProblemsCode1
Hardware Accelerator for Adversarial Attacks on Deep Learning Neural Networks0
Pseudoinverse Graph Convolutional Networks: Fast Filters Tailored for Large Eigengaps of Dense Graphs and HypergraphsCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05Unverified