Keyphrases
Functional Linear Regression
75%
Reproducing Kernel Hilbert Space
67%
Rectified Linear Unit (ReLU)
56%
Functional Data Analysis
55%
Integral Operator
52%
Regression Function
50%
Deep Convolutional Neural Network (deep CNN)
50%
Functional Linear Regression Model
50%
Reproducing Kernel
50%
Covariance Function
50%
Convolutional Neural Network
43%
Error Analysis
43%
Optimal Convergence Rate
39%
Generalization Analysis
37%
Theoretical Properties
37%
Functional Data
34%
Learning Algorithm
33%
Minimax Optimal Rate
33%
Gradient Method
31%
Loss Function
31%
Scale Parameter
31%
Robust Regression
31%
Information Theoretic Learning
31%
Learning Rate
31%
Empirical Risk Minimization
31%
Kernel Methods
31%
Data Learning
31%
Large-scale Data
27%
Learning Scheme
27%
Gradient Descent
27%
Infinite Dimension
27%
Activation Function
27%
Kernel Learning
25%
Testing Scheme
25%
Large Margin Learning
25%
Robust Loss
25%
Early Stopping Rules
25%
Scalar Response
25%
Robust Loss Function
25%
Eigenvalue Decay
25%
Distributed Gradient Descent
25%
Learning Theory
25%
Nonparametric Component
25%
Comparison Theorem
25%
Statistical Methods
25%
Smooth Functionals
25%
Optimal Prediction
25%
Explicit Learning
25%
Prediction Error
25%
High Probability
25%
Maximum Correntropy Criterion
25%
Minimization Problem
25%
Decay Rate
25%
Stable Algorithm
25%
Early Stopping
25%
Estimation Error
25%
Generalization Gap
25%
Functional Predictor
25%
Uniformly Stable
25%
Large Margin
25%
High Probability Bound
25%
Kernel-based
25%
Correntropy
25%
Response Variable
25%
Moment Conditions
25%
Nonlinear Functional
25%
Functional Learning
25%
Uniform Stability
25%
Generalization Bounds
25%
Computational Storage
25%
Highly Effective
25%
Risk Prediction
25%
Computational Complexity
25%
Computational Challenges
25%
Subsampling Methods
25%
Learning Problems
25%
Storage Requirement
25%
Neural Network
20%
Deep Learning
18%
Convergence Rate
18%
Functional Components
16%
Approximation Error
16%
Theoretical Understanding
15%
Continuous Functionals
14%
Deep Neural Network
14%
Rate of Approximation
14%
Approximation Power
14%
Outlier Detection
12%
Function Test
12%
Spectral Regularization
12%
Vector-valued Random Variables
12%
Regularization Algorithm
12%
Online Learning
12%
Convolutional Neural Network Algorithm
12%
Structured Deep Learning
12%
Gaussian Kernel
12%
Induced Loss
12%
Value Function
12%
Weakly Dependent
12%
Strongly Convex
12%
Target Function
12%
Stochastic Gradient Descent
12%
Almost Optimal
12%
Generalization Behavior
12%
Stability Measures
12%
Combined Information
12%
Sharp Bound
12%
Statistical Learning Theory
12%
Optimization Algorithm
12%
Training Examples
12%
Regression Algorithm
12%
Stability Guarantee
12%
Optimal Bound
12%
Algorithmic Stability
12%
Concentration Inequalities
12%
Korobov Space
12%
Deep Learning Model
12%
Big Data
12%
Convolutional Structure
12%
Distributed Learning
9%
Optimal Learning Rate
9%
Semi-functional Linear Model
8%
Logm
8%
Space of Analytic Functions
8%
Logarithmic Rate
8%
Representer Theorem
8%
Algorithm Efficiency
8%
Extracting Features
8%
Polynomial Rate
8%
Unit Ball
8%
Modulus of Continuity
8%
Prediction Approach
8%
High-order
8%
Novel Prediction
8%
High-order Smoothness
8%
Approximation Results
8%
Penalized Least Squares Method
8%
Functional Networks
8%
Network Structure
8%
Minimax Rate
8%
Target Functional
8%
Operator Decomposition
6%
Testing Rates
6%
Distributed Scheme
6%
Science-society
6%
Maximum Mean Discrepancy
6%
Rate Detection
6%
Order Decomposition
6%
Pairwise Classification
6%
Learning Task
6%
Kernel-based Algorithm
6%
Truncated Loss
6%
Robust Learning
6%
Modern Learning
6%
Optimal Testing
6%
Test Statistic
6%
Fast Learning Rate
6%
Goodness-of-fit Test
6%
Natural Bridges
6%
Modern Application
6%
Testing Algorithm
6%
Mathematical Theory
6%
Mean Shift Outlier Model
6%
Data Science
6%
Minimax Optimal
6%
Contaminated Data
6%
Pairwise Learning
6%
Performance Prediction
6%
Huber Loss Function
6%
Robust Performance
6%
Piecewise Linear Interpolation
6%
Ridge Structure
6%
Pth Moment
6%
Sobolev Spaces
6%
Lipschitz
6%
Deep Learning Theory
6%
Neural Network Model
6%
Distribution-based
6%
Triangulation
6%
Image Recognition
6%
Likelihood Approach
6%
Learning Framework
6%
Least Squares Loss
6%
Bioinformatics
6%
Convex Loss Function
6%
Regression Task
6%
Machine Losses
6%
Heavy-tailed Noise
6%
Fully Convolutional Neural Network
6%
High Dimension
6%
Data piling
6%
Minimax
6%
Low Sample Size
6%
Binary Classification
6%
Natural Language Processing
6%
Generalization Error
6%
FLANN
6%
Regression Problem
6%
Regularity Conditions
6%
Support Vector Machine
6%
Mathematics
Functional Data
100%
Linear Regression Analysis
75%
Loss Function
71%
Hilbert Space
70%
Regression Function
57%
Convolutional Neural Network
50%
Minimax
50%
Error Analysis
45%
Integral Operator
45%
Neural Network
41%
Continuous Functionals
37%
Approximates
37%
Deep Neural Network
37%
Covariance Function
37%
Linear Regression Model
37%
Empirical Risk Minimization
28%
Deep Learning Method
28%
Dimensional Data
25%
Probability Theory
25%
Statistical Method
25%
Pointwise
25%
Explicit Learning
25%
Comparison Theorem
25%
Stopping Rule
25%
Outlier Detection
25%
Prediction Error
25%
Eigenvalue
25%
Moment Condition
25%
Response Variable
25%
Regularization
25%
Minimization Problem
25%
Functionals
25%
Approximation Error
25%
Piecewise Linear
25%
Linear Interpolation
25%
Integer
25%
Regularity Condition
25%
Kernel Method
25%
Gaussian Distribution
20%
Convergence Rate
16%
High Probability Bound
16%
Outlier
16%
Least Square
16%
Robust Regression
16%
Difference Operator
12%
Learning Task
12%
Goodness of Fit Test
12%
Mathematical Theory
12%
Type Test Statistic
12%
Predictive Performance
12%
Mean Shift
12%
Square Method
12%
Linear Models
12%
Numerical Analysis
12%
Space of Analytic Functions
12%
Hlder Space
12%
Unit Ball
12%
Total Number
12%
Polynomial
12%
Stochastics
8%
Summation
8%
Function Value
8%
Support Vector Machine
8%
Binary Classification
8%
Sharp Bound
8%
Higher Dimensions
8%
Likelihood Approach
8%
Fundamental Concept
8%
Random Variable
8%
Classification Problem
8%
Operator Approach
8%
Single Machine
8%
Data Sample
8%
Divide and Conquer
8%
Covariate
8%
Artificial Neural Network
6%