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Additive models

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TitleStatusHype
Generalized Sparse Additive Models—0
Generalized Minkowski sets for the regularization of inverse problemsCode0
Scalable GAM using sparse variational Gaussian processes—0
Neural Interaction Transparency (NIT): Disentangling Learned Interactions for Improved Interpretability—0
Axiomatic Interpretability for Multiclass Additive ModelsCode0
Fast Automatic Smoothing for Generalized Additive Models—0
Structured nonlinear variable selectionCode0
Large-scale Nonlinear Variable Selection via Kernel Random Features—0
Performance evaluation and hyperparameter tuning of statistical and machine-learning models using spatial dataCode0
Detecting Nonlinear Causality in Multivariate Time Series with Sparse Additive Models—0
High-Dimensional Bayesian Optimization via Additive Models with Overlapping GroupsCode1
Statistical Learnability of Generalized Additive Models based on Total Variation Regularization—0
Considerations When Learning Additive Explanations for Black-Box ModelsCode0
Group Sparse Additive Machine—0
Tree-Structured Boosting: Connections Between Gradient Boosted Stumps and Full Decision Trees—0
Sparse Linear Isotonic Models—0
Multilevel Modeling with Structured Penalties for Classification from Imaging Genetics data—0
Nonparametric regression using deep neural networks with ReLU activation function—0
Interpretable Low-Dimensional Regression via Data-Adaptive Smoothing—0
Additive Component Analysis—0
Sparse hierarchical interaction learning with epigraphical projectionCode0
Convex-constrained Sparse Additive Modeling and Its Extensions—0
GapTV: Accurate and Interpretable Low-Dimensional Regression and Classification—0
Additive Models with Trend Filtering—0
Joint Semantic Synthesis and Morphological Analysis of the Derived Word—0
Stability selection for component-wise gradient boosting in multiple dimensionsCode0
Nonparametric Regression with Adaptive Truncation via a Convex Hierarchical Penalty—0
Saturating Splines and Feature Selection—0
Algorithms for Learning Sparse Additive Models with Interactions in High Dimensions—0
Chained Gaussian ProcessesCode0
Learning Sparse Additive Models with Interactions in High Dimensions—0
Additive Approximations in High Dimensional Nonparametric Regression via the SALSACode0
Electricity Demand Forecasting by Multi-Task Learning—0
Hamiltonian Monte Carlo Acceleration Using Surrogate Functions with Random BasesCode0
Generalized Additive Model Selection—0
Multi-task additive models with shared transfer functions based on dictionary learning—0
Minimax Optimal Rates of Estimation in High Dimensional Additive Models: Universal Phase Transition—0
Kernel Meets Sieve: Post-Regularization Confidence Bands for Sparse Additive Model—0
High Dimensional Bayesian Optimisation and Bandits via Additive Models—0
Efficient Sampling for Learning Sparse Additive Models in High Dimensions—0
Bus Travel Time Predictions Using Additive Models—0
Faithful Variable Screening for High-Dimensional Convex Regression—0
Sparse Partially Linear Additive ModelsCode0
Learning rates for the risk of kernel based quantile regression estimators in additive models—0
Estimating complex causal effects from incomplete observational data—0
Feature Augmentation via Nonparametrics and Selection (FANS) in High Dimensional Classification—0
CAM: Causal additive models, high-dimensional order search and penalized regression—0
Dependence Measure for non-additive model—0
Adaptive Learning of Smoothing Functions: Application to Electricity Load Forecasting—0
Additive Gaussian ProcessesCode0
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