Mathematics
Learning
100%
Multi-class
81%
Learnability
43%
Classifier
38%
Half-space
35%
Efficient Algorithms
29%
Rule Learning
25%
Revealed Preference
23%
Class
23%
Regret
22%
Distribution-free
22%
Vapnik-Chervonenkis Dimension
21%
Extractor
20%
Pseudorandom Generator
19%
Convex Optimization
19%
Online Algorithms
18%
Expander
18%
Hardness
18%
Inapproximability
18%
Competitive Ratio
18%
Activation
17%
Utility Function
17%
Margin
16%
Neural Networks
15%
Query
14%
Scenarios
13%
Economics
12%
Error Rate
12%
Lipschitz
12%
Binary Classification
11%
Generalization
11%
Activation Function
11%
Combinatorial Auctions
11%
Logarithmic
11%
Prediction
9%
Sentiment Analysis
9%
Decision tree
8%
Training
8%
Uniform distribution
8%
Line
7%
Optimization
7%
Target
7%
Budget Constraint
7%
Regular Graph
7%
Algorithmic Mechanism Design
6%
Misspecified Model
6%
Graph in graph theory
6%
Interpretability
6%
Intersection
6%
Model
6%
Engineering & Materials Science
Neural networks
92%
Hardness
71%
Polynomials
61%
Classifiers
40%
Labels
38%
Computational efficiency
28%
Machinery
28%
Chemical activation
27%
Convex optimization
18%
Computational complexity
17%
Learning algorithms
17%
Network layers
16%
Parameterization
15%
Supervised learning
15%
Adaptive algorithms
14%
Gaussian distribution
12%
Electric power distribution
11%
Decision trees
10%
Economics
9%
Error analysis
9%
Network architecture
6%
Polynomial regression
6%
Constraint satisfaction problems
6%
Servers
6%
Sentiment analysis
5%
Availability
5%