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 3976–4000 of 4891 papers

TitleStatusHype
Refining a -nearest neighbor graph for a computationally efficient spectral clusteringCode0
An Efficient Active Set Algorithm for Covariance Based Joint Data and Activity Detection for Massive Random Access with Massive MIMO—0
A Universal Framework for Featurization of Atomistic SystemsCode0
Learning the Update Operator for 2D/3D Image Registration—0
An efficient optimization based microstructure reconstruction approach with multiple loss functions—0
Gaze-based dual resolution deep imitation learning for high-precision dexterous robot manipulation—0
Comparing hundreds of machine learning classifiers and discrete choice models in predicting travel behavior: an empirical benchmark—0
A Multiscale Environment for Learning by DiffusionCode0
Improving Human Decision-Making by Discovering Efficient Strategies for Hierarchical Planning—0
Recurrent Localization Networks applied to the Lippmann-Schwinger EquationCode0
Decision Machines: Congruent Decision Trees—0
Prediction of 3D Cardiovascular hemodynamics before and after coronary artery bypass surgery via deep learning—0
Data-driven sparse polynomial chaos expansion for models with dependent inputs—0
ZeRO-Offload: Democratizing Billion-Scale Model TrainingCode0
Frequency-weighted H2-optimal model order reduction via oblique projection—0
Disentangled Self-Attentive Neural Networks for Click-Through Rate PredictionCode0
Resolution-Based Distillation for Efficient Histology Image Classification—0
A novel shape matching descriptor for real-time hand gesture recognition—0
Optimizing Over All Sequences of Orthogonal Polynomials—0
Statistically Consistent Saliency Estimation—0
A Simple Unified Information Regularization Framework for Multi-Source Domain Adaptation—0
Balancing training time vs. performance with Bayesian Early Pruning—0
Globally Optimal and Efficient Manhattan Frame Estimation by Delimiting Rotation Search Space—0
Rethinking Convolution: Towards an Optimal Efficiency—0
Estimation of Number of Communities in Assortative Sparse Networks—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified