Mathematics
Additive Noise
23%
Approximates
78%
Asymptotic Distribution
17%
Asymptotics
23%
Bounded Variation
17%
Calculus of Variations
8%
Classification Problem
34%
Clique
17%
Cluster Sampling
11%
Component Function
17%
Concludes
17%
Connected Component
34%
Constant Factor
17%
Contractive
8%
Convergence Property
8%
Convergence Rate
41%
Convex Body
11%
Cosine
17%
Covariate
20%
Decision Tree
100%
Dependent Data
24%
Dimensional Case
11%
Dimensional Distribution
11%
Effect Size
8%
End Point
11%
Error Analysis
11%
Error Bound
34%
Error Distribution
8%
Expectation-Maximization Algorithm
26%
Experimenter
11%
Fitted Model
11%
Fourier Transform
11%
Gaussian Distribution
63%
Goodness of Fit Test
24%
Gradient Flow
34%
Greedy Algorithm
11%
Hausdorff
23%
Hlder Inequality
34%
Hyperplane
11%
Induced Subgraph
34%
Initial Guess
17%
Input Vector
8%
Interpretability
11%
Joint Distribution
17%
Kernel Density
11%
Likelihood Estimator
17%
Limit Point
11%
Linear Combination
23%
Linear Models
34%
Linear Regression
55%
Linear Time
17%
Marginals
34%
Maximum Likelihood Estimation
34%
Median
34%
Minimax
29%
Model Form
11%
Model Misspecification
8%
Model Selection
11%
Neural Network
23%
Nonparametric Model
11%
Numerical Experiment
11%
Numerical Simulation
11%
Optimal Decision
41%
Optimality
11%
Ordinary Differential Equation
34%
Parameter Vector
34%
Parametric
8%
Parametric Model
17%
Partial Differential Equation
17%
Pearson Correlation
13%
Prediction Error
41%
Predictive Accuracy
11%
Predictive Model
11%
Predictor Variable
34%
Probability Theory
8%
Regression Function
34%
Regression Model
54%
Regression tree
87%
Regularization
63%
Response Data
6%
Ridge Functions
29%
Scale Model
8%
Simple Model
34%
Simulation Study
8%
Single Covariate
11%
Square Error
6%
Squared Error
11%
Statistical Mechanics
34%
Statistics
11%
Step Size
11%
Sum of Squares
6%
Supplementary Material
17%
Thompson Estimator
17%
Thresholding
11%
Tradeoff
46%
Unbiased Estimator
17%
Uniform Convergence
17%
Upper Bound
26%
Wide Range
17%
Worst Case
34%
Keyphrases
Adaptive Partitioning
17%
Additive Regression
17%
Algorithmic Analysis
69%
Algorithmic Approach
13%
Approximate Message Passing
34%
Asymptotic Dynamics
6%
Backward Error Analysis
11%
Barra
41%
Binary Split
8%
Borel Measurable
17%
Bounded Variation
17%
C4.5
17%
Calculus of Variations Problem
11%
CART Decision Tree
8%
Classification and Regression Tree
17%
Classification Task
17%
Combinatorial Complexity
17%
Component Functions
17%
Computational Tools
17%
Computer Optimization
17%
Computer Science
17%
Continuous-discrete
17%
Convergence Rate
34%
Convex Optimization
6%
Convex Optimization Problem
17%
Convex Support
34%
Cosine Angle
13%
Cost-complexity Pruning
8%
Countable Model
17%
Covariate Distribution
6%
Decision Nodes
34%
Decision Tree
52%
Dependent Data
17%
Developing States
13%
Flexible Approach
6%
Function Library
34%
Gaussian Random
6%
Goodness-of-fit
17%
Greedy Approximation Algorithm
17%
High-dimensional Regression
6%
Hlder's Inequality
34%
Horvitz-Thompson
8%
Horvitz-Thompson Estimator
8%
Hyperplane
17%
Immediate Consequences
34%
Information Theory
34%
Inner Parameters
11%
Interpolation Model
17%
Interpretable Methods
17%
Joint Distribution
17%
L1-norm
17%
Large-scale Prediction
34%
Limit Point
17%
Linear Combination
34%
Lipschitz Smoothness
13%
Matching Structure
17%
Misspecified Model
17%
Model Form
17%
Neighborhood Sampling
26%
Neural Network
34%
Non-separable
13%
Nonparametric Variable Selection
8%
Numerical Simulation
6%
Oblique Decision Trees
34%
Oblique Random Forest
17%
One Nearest Neighbour
34%
One-norm
11%
Optimal Model Selection
8%
Oracle Inequality
34%
Orthogonal Greedy Algorithm
17%
Parent Graph
17%
Parental Networks
8%
Prediction Accuracy
17%
Predictor Variables
34%
Projection Pursuit Regression
17%
Public Beliefs
17%
Qualitative Properties
17%
Random Forest
17%
Regression Model
34%
Regression Network
17%
Regression Task
17%
Regression Tree
34%
Ridge Functions
29%
Similarity Model
17%
Single Hidden Layer Neural Network
11%
Sinusoidal Model
11%
SLOPE Estimator
11%
Sparsity Constraint
17%
Split Point
17%
Squared Error
17%
State Evolution
6%
Statistical Estimation
34%
Statistical Risk
17%
Subsampled Data
8%
Sum Square Error
8%
Tree Construction
17%
Two-norm
11%
Variable Importance Measure
8%
Variational Perspective
34%
Vertex Sampling
8%
Computer Science
Approximation Algorithms
11%
Attention (Machine Learning)
34%
Computer Science
11%
Convergence Rate
34%
Convex Optimization
11%
Decision Node
23%
Decision Trees
34%
Good Classifier
34%
Gradient Descent
34%
Greedy Algorithm
11%
Hausdorff Distance
34%
Hlder Inequality
34%
Hyperplanes
11%
Interpretability
11%
Library Function
34%
Limit Point
11%
Linear Combination
23%
Machine Learning Algorithm
34%
Nearest Neighbors Classifier
34%
Neural Network
23%
Optimization Problem
11%
Prediction Rule
34%
Predictive Accuracy
11%
Random Decision Forest
11%
Regression Tree
34%
Single Covariate
11%
Theoretical Framework
58%
Training Data
34%
Tree Construction
11%
