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regression

Papers

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Showing 3576–3600 of 9424 papers

TitleStatusHype
Optimal Online Generalized Linear Regression with Stochastic Noise and Its Application to Heteroscedastic Bandits—0
Bayesian Active Learning for Discrete Latent Variable Models—0
Bayesian Ridge Regression Based Model to Predict Fault Location in HVdc Network—0
Multi-Layer Perceptron Neural Network for Improving Detection Performance of Malicious Phishing URLs Without Affecting Other Attack Types Classification—0
Scalable Gaussian-process regression and variable selection using Vecchia approximationsCode0
Learning to Liquidate Forex: Optimal Stopping via Adaptive Top-K Regression—0
ANTLER: Bayesian Nonlinear Tensor Learning and Modeler for Unstructured, Varying-Size Point Cloud Data—0
Variational inference for large Bayesian vector autoregressions—0
Reconstruction of Perceived Images from fMRI Patterns and Semantic Brain Exploration using Instance-Conditioned GANsCode1
On Monocular Depth Estimation and Uncertainty Quantification using Classification Approaches for Regression—0
Exploring the Unfairness of DP-SGD Across Settings—0
Optimal Convergence Rates of Deep Convolutional Neural Networks: Additive Ridge Functions—0
Sequential asset ranking in nonstationary time series—0
Nowcasting the Financial Time Series with Streaming Data Analytics under Apache Spark—0
Nuclei panoptic segmentation and composition regression with multi-task deep neural networks—0
Better Modelling Out-of-Distribution Regression on Distributed Acoustic Sensor Data Using Anchored Hidden State Mixup—0
Towards Speaker Age Estimation with Label Distribution Learning—0
Deep Metric Learning-Based Semi-Supervised Regression With Alternate Learning—0
An Evaluation of the EEG alpha-to-theta and theta-to-alpha band Ratios as Indexes of Mental Workload—0
From Optimization Dynamics to Generalization Bounds via Łojasiewicz Gradient Inequality—0
Confident Neural Network Regression with Bootstrapped Deep EnsemblesCode0
Distilled Neural Networks for Efficient Learning to RankCode0
Honour Thesis: A Joint Value at Risk and Expected Shortfall Combination Framework and its Applications in the Cryptocurrency Market—0
Estimation of Evaporator Valve Sizes in Supermarket Refrigeration Cabinets—0
Memorize to Generalize: on the Necessity of Interpolation in High Dimensional Linear Regression—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