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regression

Papers

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Showing 5101–5150 of 9424 papers

TitleStatusHype
Model-based Reinforcement Learning for Continuous Control with Posterior SamplingCode0
Optimizing Approximate Leave-one-out Cross-validation to Tune HyperparametersCode1
On the coercivity condition in the learning of interacting particle systems—0
ANIMC: A Soft Framework for Auto-weighted Noisy and Incomplete Multi-view ClusteringCode0
Anderson acceleration of coordinate descent—0
Learning to Predict the 3D Layout of a Scene—0
Dense Label Encoding for Boundary Discontinuity Free Rotation DetectionCode1
A Risk Based approach for the Solvency Capital requirement for Health Plans—0
SoftSeg: Advantages of soft versus binary training for image segmentation—0
Beyond Pinball Loss: Quantile Methods for Calibrated Uncertainty QuantificationCode2
Masked Linear Regression for Learning Local Receptive Fields for Facial Expression Synthesis—0
Combining Prosodic, Voice Quality and Lexical Features to Automatically Detect Alzheimer's Disease—0
A Discussion on Practical Considerations with Sparse Regression Methodologies—0
Positive-Congruent Training: Towards Regression-Free Model Updates—0
Machine-Learning Number Fields—0
VIB is Half Bayes—0
Developing an Effective and Automated Patient Engagement Estimator for Telehealth: A Machine Learning Approach—0
Avoiding Communication in Logistic Regression—0
IIT_kgp at FinCausal 2020, Shared Task 1: Causality Detection using Sentence Embeddings in Financial Reports—0
Continuous Conditional Generative Adversarial Networks: Novel Empirical Losses and Label Input MechanismsCode1
Deep Ordinal Regression using Optimal Transport Loss and Unimodal Output Probabilities—0
Accelerating Distributed SGD for Linear Regression using Iterative Pre-Conditioning—0
Gaussian Process-based Min-norm Stabilizing Controller for Control-Affine Systems with Uncertain Input Effects and Dynamics—0
Formation of Regression Model for Analysis of Complex Systems Using Methodology of Genetic Algorithms—0
Toward the Fully Physics-Informed Echo State Network -- an ODE Approximator Based on Recurrent Artificial Neurons—0
Regression Trees for Cumulative Incidence Functions—0
Non-stationary Online Regression—0
Determinantal Point Processes Implicitly Regularize Semi-parametric Regression Problems—0
Gaussian Transforms Modeling and the Estimation of Distributional Regression Functions—0
Relative Lipschitzness in Extragradient Methods and a Direct Recipe for Acceleration—0
Node Attribute Completion in Knowledge Graphs with Multi-Relational PropagationCode0
Causality-aware counterfactual confounding adjustment as an alternative to linear residualization in anticausal prediction tasks based on linear learners—0
Sparsely constrained neural networks for model discovery of PDEsCode1
Spring-Rod System Identification via Differentiable Physics Engine—0
Google Trends Analysis of COVID-19—0
Deeply-Supervised Density Regression for Automatic Cell Counting in Microscopy Images—0
Graph Kernels: State-of-the-Art and Future ChallengesCode1
Curse of Small Sample Size in Forecasting of the Active Cases in COVID-19 Outbreak—0
Estimation, Confidence Intervals, and Large-Scale Hypotheses Testing for High-Dimensional Mixed Linear Regression—0
Fighting an Infodemic: COVID-19 Fake News DatasetCode1
Sparse Approximate Solutions to Max-Plus Equations with Application to Multivariate Convex Regression—0
Deep learning architectures for inference of AC-OPF solutions—0
Wasserstein-based fairness interpretability framework for machine learning models—0
Fault Location Estimation by Using Machine Learning Methods in Mixed Transmission Lines—0
Ridge Regression with Frequent Directions: Statistical and Optimization Perspectives—0
Beyond Marginal Uncertainty: How Accurately can Bayesian Regression Models Estimate Posterior Predictive Correlations?Code0
Bias correction for quantile regression estimators—0
QMUL-SDS @ DIACR-Ita: Evaluating Unsupervised Diachronic Lexical Semantics Classification in Italian—0
A Follow-the-Leader Strategy using Hierarchical Deep Neural Networks with Grouped Convolutions—0
Gradient-Based Empirical Risk Minimization using Local Polynomial 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