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regression

Papers

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Showing 1001–1050 of 9424 papers

TitleStatusHype
Agreement Prediction of Arguments in Cyber Argumentation for Detecting Stance Polarity and Intensity—0
A snapshot on nonstandard supervised learning problems: taxonomy, relationships and methods—0
A Societal Sentiment Analysis: Predicting the Values and Ethics of Individuals by Analysing Social Media Content—0
A Solver + Gradient Descent Training Algorithm for Deep Neural Networks—0
A Sparse Gaussian Process Framework for Photometric Redshift Estimation—0
A sparse PAC-Bayesian approach for high-dimensional quantile prediction—0
Approximation of RKHS Functionals by Neural Networks—0
A Gaussian Process Regression Model for Distribution Inputs—0
A spectral algorithm for robust regression with subgaussian rates—0
A spectral least-squares-type method for heavy-tailed corrupted regression with unknown covariance \& heterogeneous noise—0
Approximation Guarantees of Local Search Algorithms via Localizability of Set Functions—0
A Spectral Series Approach to High-Dimensional Nonparametric Regression—0
A Hierarchical Bayesian Linear Regression Model with Local Features for Stochastic Dynamics Approximation—0
A spectrum of physics-informed Gaussian processes for regression in engineering—0
Approximation Bounds for Transformer Networks with Application to Regression—0
Assessing high-order effects in feature importance via predictability decomposition—0
Assessing Quality Estimation Models for Sentence-Level Prediction—0
Assessing Quantum Advantage for Gaussian Process Regression—0
A Gaussian Process Regression based Dynamical Models Learning Algorithm for Target Tracking—0
Assessing the Prosody of Non-Native Speakers of English: Measures and Feature Sets—0
Assessing univariate and bivariate risks of late-frost and drought using vine copulas: A historical study for Bavaria—0
Assessment and treatment of visuospatial neglect using active learning with Gaussian processes regression—0
Active Heteroscedastic Regression—0
Approximation Bounds for Recurrent Neural Networks with Application to Regression—0
Approximation bounds for norm constrained neural networks with applications to regression and GANs—0
A Gaussian Process-based Price-Amount Curve Construction for Demand Response Provided by Internet Data Centers—0
Approximating Score-based Explanation Techniques Using Conformal Regression—0
Approximating Optimal Estimation of Time Offset Synchronization with Temperature Variations—0
A Gaussian Process Based Method with Deep Kernel Learning for Pricing High-dimensional American Options—0
Active Exploration in Iterative Gaussian Process Regression for Uncertainty Modeling in Autonomous Racing—0
3D Human Pose Estimation from a Single Image via Distance Matrix Regression—0
Approximate Steepest Coordinate Descent—0
Approximate Leave-one-out Cross Validation for Regression with _1 Regularizers (extended version)—0
A Fuzzy-set-based Joint Distribution Adaptation Method for Regression and its Application to Online Damage Quantification for Structural Digital Twin—0
Approximate Inference for Nonstationary Heteroscedastic Gaussian process Regression—0
A Fused Elastic Net Logistic Regression Model for Multi-Task Binary Classification—0
ActiveClean: Interactive Data Cleaning While Learning Convex Loss Models—0
Automated Focal Loss for Image based Object Detection—0
Approximate Gaussian process inference for the drift function in stochastic differential equations—0
Approximated Orthogonal Projection Unit: Stabilizing Regression Network Training Using Natural Gradient—0
A Fundamental Accuracy--Robustness Trade-off in Regression and Classification—0
Approximate cross-validation formula for Bayesian linear regression—0
A Functional Regression approach to Facial Landmark Tracking—0
Accelerating L-shaped Two-stage Stochastic SCUC with Learning Integrated Benders Decomposition—0
Automated Learning of Interpretable Models with Quantified Uncertainty—0
Automated Model Selection for Generalized Linear Models—0
Approximate Bayes learning of stochastic differential equations—0
Applying SVGD to Bayesian Neural Networks for Cyclical Time-Series Prediction and Inference—0
A Functional Analysis Approach to Symbolic Regression—0
Applying Regression Conformal Prediction with Nearest Neighbors to time series data—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