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 48014850 of 4891 papers

TitleStatusHype
Scalable Nonlinear Learning with Adaptive Polynomial Expansions0
Backhaul-Constrained Multi-Cell Cooperation Leveraging Sparsity and Spectral Clustering0
Extracting man-made objects from remote sensing images via fast level set evolutions0
An inexact Newton-Krylov algorithm for constrained diffeomorphic image registration0
Improved Distributed Principal Component Analysis0
Statistical and computational trade-offs in estimation of sparse principal components0
Bi-l0-l2-Norm Regularization for Blind Motion Deblurring0
Object Proposal Generation using Two-Stage Cascade SVMs0
Generalized Higher-Order Tensor Decomposition via Parallel ADMM0
Sparse Estimation with the Swept Approximated Message-Passing AlgorithmCode0
Bayesian Optimal Control of Smoothly Parameterized Systems: The Lazy Posterior Sampling Algorithm0
Semantic Graph for Zero-Shot Learning0
Eigenspace Method for Spatiotemporal Hotspot Detection0
Algebraic-Combinatorial Methods for Low-Rank Matrix Completion with Application to Athletic Performance Prediction0
Shrinkage Fields for Effective Image Restoration0
Efficient Computation of Relative Pose for Multi-Camera Systems0
Inference of Sparse Networks with Unobserved Variables. Application to Gene Regulatory NetworksCode0
Off-Policy Shaping Ensembles in Reinforcement Learning0
Single camera pose estimation using Bayesian filtering and Kinect motion priorsCode0
Fast Ridge Regression with Randomized Principal Component Analysis and Gradient Descent0
A Rank-SVM Approach to Anomaly Detection0
Bayesian Neural Networks for Genetic Association Studies of Complex DiseaseCode0
Distribution-Aware Sampling and Weighted Model Counting for SAT0
Don't Fall for Tuning Parameters: Tuning-Free Variable Selection in High Dimensions With the TREX0
Correlation Filters with Limited Boundaries0
Matroid Bandits: Fast Combinatorial Optimization with Learning0
Data-driven HRF estimation for encoding and decoding models0
Binary Stereo MatchingCode0
A high-reproducibility and high-accuracy method for automated topic classification0
Approximate Model-Based Diagnosis Using Greedy Stochastic Search0
Smart machines and the SP theory of intelligence0
The return of AdaBoost.MH: multi-class Hamming trees0
Parallelizing MCMC via Weierstrass SamplerCode0
Reconciling "priors" & "priors" without prejudice?0
Bayesian inference for low rank spatiotemporal neural receptive fields0
A* Lasso for Learning a Sparse Bayesian Network Structure for Continuous Variables0
Global Solver and Its Efficient Approximation for Variational Bayesian Low-rank Subspace Clustering0
Simultaneous Rectification and Alignment via Robust Recovery of Low-rank Tensors0
Factorized Asymptotic Bayesian Inference for Latent Feature Models0
Learning Pairwise Graphical Models with Nonlinear Sufficient Statistics0
Fast large-scale optimization by unifying stochastic gradient and quasi-Newton methodsCode0
Efficient State-Space Inference of Periodic Latent Force Models0
A Robust Variational Model for Positive Image Deconvolution0
MINT: Mutual Information based Transductive Feature Selection for Genetic Trait Prediction0
Electricity Market Forecasting via Low-Rank Multi-Kernel Learning0
Cross-Recurrence Quantification Analysis of Categorical and Continuous Time Series: an R package0
Context-aware recommendations from implicit data via scalable tensor factorization0
Feature Extraction of Hyperspectral Images With Image Fusion and Recursive Filtering0
Online Tensor Methods for Learning Latent Variable ModelsCode0
DeBaCl: A Python Package for Interactive DEnsity-BAsed CLusteringCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05Unverified