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 4876–4891 of 4891 papers

TitleStatusHype
Efficient Regularized Least-Squares Algorithms for Conditional Ranking on Relational Data—0
A Comparative Study of Efficient Initialization Methods for the K-Means Clustering AlgorithmCode0
Graph Degree Linkage: Agglomerative Clustering on a Directed GraphCode0
Bayesian inference for logistic models using Polya-Gamma latent variablesCode1
Fast ALS-based tensor factorization for context-aware recommendation from implicit feedback—0
Query-Aware MCMC—0
Learning to Search Efficiently in High Dimensions—0
Simultaneous Sampling and Multi-Structure Fitting with Adaptive Reversible Jump MCMC—0
MissForest - nonparametric missing value imputation for mixed-type data—0
Fast global convergence rates of gradient methods for high-dimensional statistical recovery—0
Efficient Relational Learning with Hidden Variable Detection—0
Time-Varying Dynamic Bayesian Networks—0
Fast Graph Laplacian Regularized Kernel Learning via Semidefinite–Quadratic–Linear Programming—0
Inter-domain Gaussian Processes for Sparse Inference using Inducing Features—0
The Ordered Residual Kernel for Robust Motion Subspace Clustering—0
Group Sparse Coding—0
Show:102550
← PrevPage 196 of 196Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified