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 4501–4525 of 4891 papers

TitleStatusHype
A Single Shot Text Detector with Scale-adaptive Anchors—0
Stochastic Layer-Wise Precision in Deep Neural Networks—0
Deep convolutional encoder-decoder networks for uncertainty quantification of dynamic multiphase flow in heterogeneous mediaCode0
An Efficient Approach to Encoding Context for Spoken Language Understanding—0
Efficient and Consistent Adversarial Bipartite Matching—0
Stochastic PCA with _2 and _1 Regularization—0
Fast CapsNet for Lung Cancer ScreeningCode0
Supervised Fuzzy Partitioning—0
An Online Prediction Algorithm for Reinforcement Learning with Linear Function Approximation using Cross Entropy Method—0
Attentive cross-modal paratope prediction—0
Knowledge Distillation by On-the-Fly Native EnsembleCode0
Composite Marginal Likelihood Methods for Random Utility Models—0
ICE-BA: Incremental, Consistent and Efficient Bundle Adjustment for Visual-Inertial SLAMCode0
HydraNets: Specialized Dynamic Architectures for Efficient Inference—0
A Fast and Scalable Joint Estimator for Integrating Additional Knowledge in Learning Multiple Related Sparse Gaussian Graphical ModelsCode0
Fast Incremental von Neumann Graph Entropy Computation: Theory, Algorithm, and ApplicationsCode0
Core Conflictual Relationship: Text Mining to Discover What and When—0
On the Estimation of Entropy in the FastICA AlgorithmCode0
Ergodic Inference: Accelerate Convergence by Optimisation—0
Quantizing Convolutional Neural Networks for Low-Power High-Throughput Inference Engines—0
Exp-Concavity of Proper Composite Losses—0
Multi-level Wavelet-CNN for Image RestorationCode0
Automated Process Planning for Hybrid Manufacturing—0
Dyna: A Method of Momentum for Stochastic Optimization—0
Neural Open Information Extraction—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified