Mathematics
Gaussian Process
100%
Bounds
50%
Kriging
50%
Parameters
45%
Bayesian
44%
Number
36%
Classes
36%
Minimax
36%
Tradeoff
33%
Variance
33%
Probability Theory
25%
Poisson Point Process
25%
Gaussian
25%
Square Estimator
25%
Linear Regression Model
25%
Optimal Estimator
22%
Bayesian Analysis
20%
Frequentist
20%
Regression Function
19%
Transfer Learning
16%
Local Convergence
16%
Random Coefficient Model
16%
Samples
16%
Joint Density
16%
Bayesian Approach
16%
General Result
16%
Variance Estimation
16%
Sample Size
16%
Compound Poisson Process
16%
Deep Neural Network
16%
Transfer Learning
16%
Matrix (Mathematics)
16%
Measures
16%
Tradeoff
16%
Worst Case
16%
Nonparametric Density Estimation
16%
Vapnik-Chervonenkis Dimension
16%
Linear Models
16%
Regularization
16%
Asymptotics
16%
Learning Rule
16%
Repeated Sampling
16%
Regression Model
16%
Additive Function
16%
Maximum Likelihood Estimator
12%
Marginal Posterior
12%
Simulation Study
12%
Supplementary Material
11%
Underlying Structure
11%
Convergence Rate
11%
Computer Science
Models
27%
Deep Neural Network
22%
Functions
16%
Random Coefficient Model
16%
Probability
16%
Activation Function
16%
Multiclass Classification
16%
Convergence Rate
16%
Neural Network
16%
Regression Parameter
16%
Gradient Descent
16%
Classes
12%
Network Architecture
11%
Data Processing
8%
Regression Function
5%
Structural Constraint
5%
Feedforward Neural Network
5%
Neural Network Architecture
5%
Sparsity
5%
Roles
5%
Network Parameter
5%
Economics, Econometrics and Finance
Measure of Dispersion
50%
Estimation Theory
41%
Information
38%
Transfers
33%
Gaussian Process
33%
Bayesian
27%
Learning
16%
Linear Regression Model
10%
