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regression

Papers

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Showing 4376–4400 of 9424 papers

TitleStatusHype
Dyadic Regression—0
DUTH at SemEval-2021 Task 7: Is Conventional Machine Learning for Humorous and Offensive Tasks enough in 2021?—0
Beyond Least-Squares: Fast Rates for Regularized Empirical Risk Minimization through Self-Concordance—0
Theoretical and Experimental Analysis on the Generalizability of Distribution Regression Network—0
A Distributionally Robust Approach to Fair Classification—0
A Comparison of Statistical and Machine Learning Algorithms for Predicting Rents in the San Francisco Bay Area—0
A Block Regression Model for Short-Term Mobile Traffic Forecasting—0
DUTH at SemEval-2017 Task 5: Sentiment Predictability in Financial Microblogging and News Articles—0
Duluth at SemEval-2020 Task 12: Offensive Tweet Identification in English with Logistic Regression—0
Duluth at SemEval-2019 Task 4: The Pioquinto Manterola Hyperpartisan News Detector—0
An Efficient Multi Quantile Regression Network with Ad Hoc Prevention of Quantile Crossing—0
Dual Path Networks for Multi-Person Human Pose Estimation—0
Dual optimization for convex constrained objectives without the gradient-Lipschitz assumption—0
An efficient model-free estimation of multiclass conditional probability—0
A Distributed Lag Approach to the Generalised Dynamic Factor Model (GDFM)—0
Dual Linear Regression Based Classification for Face Cluster Recognition—0
Beyond Beats: A Recipe to Song Popularity? A machine learning approach—0
Beware of Validation by Eye: Visual Validation of Linear Trends in Scatterplots—0
An Efficient Method of Training Small Models for Regression Problems with Knowledge Distillation—0
Dual Grid Net: hand mesh vertex regression from single depth maps—0
Dual Control for Approximate Bayesian Reinforcement Learning—0
Better Private Linear Regression Through Better Private Feature Selection—0
An Efficient Method for Face Quality Assessment on the Edge—0
A Discussion on Practical Considerations with Sparse Regression Methodologies—0
Drug Repurposing Targeting COVID-19 3CL Protease using Molecular Docking and Machine Learning Regression Approach—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