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regression

Papers

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Showing 801–825 of 9424 papers

TitleStatusHype
Constant Stepsize Local GD for Logistic Regression: Acceleration by Instability—0
Meta Optimality for Demographic Parity Constrained Regression via Post-Processing—0
From Empirical Evaluation to Context-Aware Enhancement: Repairing Regression Errors with LLMs—0
Machine Learning-Driven Compensation for Non-Ideal Channels in AWG-Based FBG Interrogator—0
Gradient Boosting for Spatial Regression Models with Autoregressive Disturbances—0
Optimizing Blood Transfusions and Predicting Shortages in Resource-Constrained Areas—0
Fidelity Isn't Accuracy: When Linearly Decodable Functions Fail to Match the Ground TruthCode0
Coefficient Shape Transfer Learning for Functional Linear Regression—0
An Interpretable Machine Learning Approach in Predicting Inflation Using Payments System Data: A Case Study of Indonesia—0
Understanding In-Context Learning on Structured Manifolds: Bridging Attention to Kernel Methods—0
Demystifying Spectral Feature Learning for Instrumental Variable Regression—0
Diffusion index forecasts under weaker loadings: PCA, ridge regression, and random projections—0
Diffuse and Disperse: Image Generation with Representation Regularization—0
Robust Visual Localization via Semantic-Guided Multi-Scale Transformer—0
Improved Scaling Laws in Linear Regression via Data Reuse—0
The Impact of Feature Scaling In Machine Learning: Effects on Regression and Classification Tasks—0
Sparse Interpretable Deep Learning with LIES Networks for Symbolic RegressionCode0
Nearness of Neighbors Attention for Regression in Supervised FinetuningCode0
Differentially Private Sparse Linear Regression with Heavy-tailed Responses—0
Membership Inference Attacks for Unseen Classes—0
On Efficient Estimation of Distributional Treatment Effects under Covariate-Adaptive RandomizationCode0
Privacy Amplification Through Synthetic Data: Insights from Linear Regression—0
Structure-Aware Radar-Camera Depth Estimation—0
When can in-context learning generalize out of task distribution?—0
Distributional encoding for Gaussian process regression with qualitative inputs—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