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regression

Papers

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Showing 4176–4200 of 9424 papers

TitleStatusHype
Efficient sampling for Gaussian linear regression with arbitrary priors—0
A New Covariance Estimator for Sufficient Dimension Reduction in High-Dimensional and Undersized Sample Problems—0
Efficient Regularized Regression for Variable Selection with L0 Penalty—0
Efficient Regularized Piecewise-Linear Regression Trees—0
Efficient Regularized Least-Squares Algorithms for Conditional Ranking on Relational Data—0
Efficient Regression in Metric Spaces via Approximate Lipschitz Extension—0
Advanced Models for Hourly Marginal CO2 Emission Factor Estimation: A Synergy between Fundamental and Statistical Approaches—0
A Comprehensive Approach to Universal Piecewise Nonlinear Regression Based on Trees—0
A Bound on the Maximal Marginal Degrees of Freedom—0
Efficient Rate Optimal Regret for Adversarial Contextual MDPs Using Online Function Approximation—0
Efficient Path Algorithms for Clustered Lasso and OSCAR—0
BLP -- Boundary Likelihood Pinpointing Networks for Accurate Temporal Action Localization—0
Efficient Pairwise Learning Using Kernel Ridge Regression: an Exact Two-Step Method—0
Efficient Optimization for Sparse Gaussian Process Regression—0
Block Variable Selection in Multivariate Regression and High-dimensional Causal Inference—0
A new Bayesian ensemble of trees classifier for identifying multi-class labels in satellite images—0
Efficient Optimization Algorithms for Linear Adversarial Training—0
Block stochastic gradient iteration for convex and nonconvex optimization—0
Efficient Online Hyperparameter Optimization for Kernel Ridge Regression with Applications to Traffic Time Series Prediction—0
Efficient Normalized Conformal Prediction and Uncertainty Quantification for Anti-Cancer Drug Sensitivity Prediction with Deep Regression Forests—0
Blocked Clusterwise Regression—0
Advanced Displacement Magnitude Prediction in Multi-Material Architected Lattice Structure Beams Using Physics Informed Neural Network Architecture—0
Efficient Multiscale Gaussian Process Regression using Hierarchical Clustering—0
Efficient Multiple Incremental Computation for Kernel Ridge Regression with Bayesian Uncertainty Modeling—0
Block building programming for symbolic regression—0
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All datasetsCalifornia Housing PricesConcrete Compressive StrengthMedical Cost Personal DatasetSynthetic: y = x * sin xADORECar_Price_Prediction

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Neural NetworkR2 Score0.79—Unverified
2Baseline RegressionR2 Score0.58—Unverified
3Mimic / SurrogateR2 Score0.57—Unverified
#ModelMetricClaimedVerifiedStatus
1Neural NetworkR2 Score0.86—Unverified
2Baseline RegressionR2 Score0.59—Unverified
3Mimic / SurrogateR2 Score0.58—Unverified
#ModelMetricClaimedVerifiedStatus
1Neural NetworkR2 Score0.87—Unverified
2Baseline RegressionR2 Score0.78—Unverified
3Mimic / SurrogateR2 Score0.78—Unverified
#ModelMetricClaimedVerifiedStatus
1Neural NetworkR2 Score0.98—Unverified
2Baseline RegressionR2 Score-0.01—Unverified
3Mimic / SurrogateR2 Score-0.01—Unverified
#ModelMetricClaimedVerifiedStatus
1XGBoost-MACCSmicro-averaged RMSE0.93—Unverified
2RF-ToxPrintchemical macro-average RMSE0.85—Unverified
#ModelMetricClaimedVerifiedStatus
1Linear and Decision Tree RegressionR Squared86.84—Unverified