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regression

Papers

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Showing 4151–4200 of 9424 papers

TitleStatusHype
Electricity Demand Forecasting with Hybrid Statistical and Machine Learning Algorithms: Case Study of Ukraine—0
Electoral David vs Goliath: How does the Spatial Concentration of Electors affect District-based Elections?—0
Elastic-net Regularized High-dimensional Negative Binomial Regression: Consistency and Weak Signals Detection—0
EiTAKA at SemEval-2018 Task 1: An Ensemble of N-Channels ConvNet and XGboost Regressors for Emotion Analysis of Tweets—0
Boosting as a kernel-based method—0
EFMVFL: An Efficient and Flexible Multi-party Vertical Federated Learning without a Third Party—0
Efficient Two-Stage Gaussian Process Regression Via Automatic Kernel Search and Subsampling—0
A new LDA formulation with covariates—0
Advanced Variations of Two-Dimensional Principal Component Analysis for Face Recognition—0
Non-invasive Liver Fibrosis Screening on CT Images using Radiomics—0
Efficient Tensor Kernel methods for sparse regression—0
Boosted Histogram Transform for Regression—0
Efficient Symmetric Norm Regression via Linear Sketching—0
Efficient Sublinear-Regret Algorithms for Online Sparse Linear Regression with Limited Observation—0
Boosted Fitted Q-Iteration—0
A new Edge Detector Based on Parametric Surface Model: Regression Surface Descriptor—0
Efficient Strongly Polynomial Algorithms for Quantile Regression—0
Efficient Spatio-Temporal Gaussian Regression via Kalman Filtering—0
BooST: Boosting Smooth Trees for Partial Effect Estimation in Nonlinear Regressions—0
Efficient Sparse Least Absolute Deviation Regression with Differential Privacy—0
A New Deterministic Technique for Symbolic Regression—0
Advanced Stationary and Non-Stationary Kernel Designs for Domain-Aware Gaussian Processes—0
Efficient Sensor Placement from Regression with Sparse Gaussian Processes in Continuous and Discrete Spaces—0
Efficient semi-supervised inference for logistic regression under case-control studies—0
Efficient Sampling for Gaussian Process Inference using Control Variables—0
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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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