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regression

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Showing 3726–3750 of 9424 papers

TitleStatusHype
Generalization Certificates for Adversarially Robust Bayesian Linear Regression—0
Generalization Error Bounds for Multiclass Sparse Linear Classifiers—0
Generalization Error Curves for Analytic Spectral Algorithms under Power-law Decay—0
Generalization Error for Linear Regression under Distributed Learning—0
Generalization error in high-dimensional perceptrons: Approaching Bayes error with convex optimization—0
Generalization error minimization: a new approach to model evaluation and selection with an application to penalized regression—0
Conditional Rank-Rank Regression—0
Generalization error of random features and kernel methods: hypercontractivity and kernel matrix concentration—0
Generalization Error Rates in Kernel Regression: The Crossover from the Noiseless to Noisy Regime—0
Generalization Errors and Learning Curves for Regression with Multi-task Gaussian Processes—0
Double Descent and Overfitting under Noisy Inputs and Distribution Shift for Linear Denoisers—0
Generalization for Least Squares Regression With Simple Spiked Covariances—0
Generalization in Kernel Regression Under Realistic Assumptions—0
Generalization in Supervised Learning Through Riemannian Contraction—0
Attribute Efficient Linear Regression with Data-Dependent Sampling—0
Generalization Properties of hyper-RKHS and its Applications—0
Conditional Uncorrelation and Efficient Non-approximate Subset Selection in Sparse Regression—0
Generalized Ambiguity Decomposition for Understanding Ensemble Diversity—0
Generalized Bayesian Additive Regression Trees Models: Beyond Conditional Conjugacy—0
Generalized Beta Mixtures of Gaussians—0
Chernoff Sampling for Active Testing and Extension to Active Regression—0
Conditioned Regression Models for Non-Blind Single Image Super-Resolution—0
A regression algorithm for accelerated lattice QCD that exploits sparse inference on the D-Wave quantum annealer—0
Conditioning of Random Feature Matrices: Double Descent and Generalization Error—0
Deep Gaussian Processes for Regression using Approximate Expectation Propagation—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