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

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Showing 4701–4725 of 4891 papers

TitleStatusHype
The constrained Dantzig selector with enhanced consistency—0
Distributed Flexible Nonlinear Tensor Factorization—0
An improved chromosome formulation for genetic algorithms applied to variable selection with the inclusion of interaction terms—0
Online Human Action Detection using Joint Classification-Regression Recurrent Neural NetworksCode0
An Initial Seed Selection Algorithm for K-means Clustering of Georeferenced Data to Improve Replicability of Cluster Assignments for Mapping Application—0
Distribution-Free Predictive Inference For RegressionCode0
Online Nonnegative Matrix Factorization with Outliers—0
A Semi-Lagrangian two-level preconditioned Newton-Krylov solver for constrained diffeomorphic image registration—0
The deterministic information bottleneckCode0
An Empirical Study of Dimensional Reduction Techniques for Facial Action Units Detection—0
Scalable Bayesian Rule ListsCode0
Clustering with a Reject Option: Interactive Clustering as Bayesian Prior Elicitation—0
Depth-Based Object Tracking Using a Robust Gaussian FilterCode0
A Harmonic Extension Approach for Collaborative Ranking—0
Variational Hamiltonian Monte Carlo via Score Matching—0
Learning Minimum Volume Sets and Anomaly Detectors from KNN Graphs—0
The demodulated band transformCode0
Sub-Sampled Newton Methods II: Local Convergence Rates—0
Simple, Robust and Optimal Ranking from Pairwise Comparisons—0
Successive Ray Refinement and Its Application to Coordinate Descent for LASSO—0
Compressed Dynamic Mode Decomposition for Background Modeling—0
Hierarchical Sparse Modeling: A Choice of Two Group Lasso Formulations—0
A New Statistical Framework for Genetic Pleiotropic Analysis of High Dimensional Phenotype Data—0
Pan-Sharpening With a Hyper-Laplacian Penalty—0
Efficient Video Segmentation Using Parametric Graph Partitioning—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified