Keyphrases
Stochastic Convex Optimization
50%
Sample Complexity
43%
Gradient Descent
34%
Regret Bounds
33%
Regret
33%
Stochastic Gradient Descent
32%
Low-rank
23%
Littlestone Dimension
23%
Concept Classes
22%
Differentially Private
21%
Switching Costs
20%
Online Learning
19%
Buyers
15%
Gradient Regularization
15%
Movement Cost
15%
Bandits
15%
Generalization Performance
15%
Proper Learning
14%
Kernel Methods
14%
Learning Algorithm
14%
Tight
13%
Uniform Convergence
12%
Mistake Bound
12%
Optimal Regret
11%
Learnability
11%
Minimax
11%
Multi-arm Bandit
11%
PAC Learning
11%
Implicit Bias
11%
Prediction with Expert Advice
11%
Prediction Problems
11%
Algorithmic Stability
11%
Neural Network
11%
Tight Bounds
10%
Optimization Algorithm
10%
Combinatorial Characterization
10%
Agnostic Learning
10%
Seller
9%
Generalization Bounds
9%
Convex Optimization Problem
9%
Adversary
9%
VC-dimension
8%
Accuracy Parameters
8%
Lipschitz Loss
8%
Empirical Risk
8%
Generalization Ability
8%
Population Risk
7%
Compact Set
7%
Online Mirror Descent
7%
Regularizer
7%
Computer Science
Convex Optimization
42%
Gradient Descent
26%
Online Learning
23%
Learning Algorithm
20%
Efficient Algorithm
17%
Neural Network
16%
Support Vector Machine
15%
Dimensional Subspace
15%
Linear Classifier
15%
Regularization
14%
Mutual Information
13%
Optimization Problem
13%
Learning Problem
11%
Kernel Method
10%
Labeled Example
10%
Optimization Algorithm
9%
Case Study
9%
Risk Population
7%
Common Ancestor
7%
Instantiation
7%
Communication Complexity
7%
Valued Function
7%
Complexity Result
7%
Pricing Problem
7%
Geometric Interpretation
7%
Classification Problem
7%
Complexity Measure
7%
Metric Space
7%
Computational Efficiency
7%
Classification Accuracy
7%
Affine Invariant
7%
Classification Task
7%
Stochastic Model
7%
Training Example
7%
Neural Network Training
7%
Dimensional Structure
7%
Random Variable
7%
Sufficient Number
7%
Regression Task
7%
Easy Direction
7%
Representation Learning
7%
Adversarial Setting
7%
Constraint Satisfaction Problems
7%
Linear Representation
7%
Network Layer
7%
Expressive Power
7%
Discretization
7%
Minimax Theorem
7%
Binary Tree
7%
Adversarial Model
7%
Mathematics
Stochastics
100%
Regularization
31%
Approximates
23%
Upper Bound
21%
Uniform Convergence
18%
Minimax
17%
Open Question
16%
Fixed Price
15%
Dimensional Subspace
15%
Loss Function
15%
Learning Task
15%
Open Problem
14%
Mutual Information
13%
VC Dimension
12%
Data Point
11%
Polynomial
10%
Wide Range
10%
Kernel Method
9%
Geometric Interpretation
7%
Expressiveness
7%
Synthetic Data
7%
Covering Number
7%
Action Space
7%
Minkowski Dimension
7%
Ext
7%
Step Size
7%
Expressive Power
7%
Stochastic Model
7%
Finite Metric Space
7%
Worst Case
7%
Multiplicative Weight
7%
Discretization
7%
Extreme Points
7%
Classification Problem
7%
Dimensional Structure
7%
Binary Tree
7%
Conditionals
6%
Compact Set
5%
Banach Space
5%
Linear Function
5%
