Mathematics
Gradient Descent
69%
Sketching
38%
Random Projection
37%
Neural Networks
34%
High-dimensional Data
32%
Structure Learning
27%
Learning
25%
Communication
25%
Recovery
25%
Converge
25%
Initialization
25%
Lasso
24%
Learnability
23%
Gradient Method
22%
Graphical Models
20%
Distributed Optimization
20%
Importance Sampling
20%
Black Box
20%
Mixed Model
19%
Model Selection
17%
Stochastic Gradient
17%
Statistical Inference
16%
Dimensionality
16%
Higher Dimensions
16%
Stable Manifold
15%
First-order
15%
Loss Function
15%
Margin
15%
Gradient Algorithm
14%
Primal-dual
14%
Distributed Estimation
14%
Optimality
14%
Local Minimizer
14%
Model
14%
Discrete Variables
14%
Sample Size
13%
Alternating Least Squares
13%
Continuous Variables
12%
Estimator
12%
Activation
12%
Norm
12%
Matrix Completion
12%
Primal-dual Algorithm
11%
Subgradient Method
11%
Proximal Methods
11%
Parametrization
11%
Framework
11%
Composite function
11%
Newton-type Methods
11%
Matrix Factorization
10%
Optimization
10%
Machine Learning
10%
Nonconvex Optimization
10%
Confidence interval
10%
M-estimator
10%
Pairwise
10%
Eigenspace
10%
Stochastic Methods
10%
Global Minimum
9%
Mirror
9%
Dynamical system
9%
Convex function
9%
Local Minima
9%
Principal Component Analysis
9%
Surrogate
9%
Systems Theory
9%
Saddlepoint
9%
Descent
8%
High-dimensional
8%
Replacement
8%
Stationary Solutions
8%
Hypothesis Testing
8%
Policy
8%
Minimizer
8%
Statistical Learning
8%
Preconditioning
7%
Unknown
7%
Valid
7%
Linear regression
7%
Process Optimization
7%
Ensemble Methods
7%
Class
6%
Programming Environments
6%
Penalization
6%
Gaussian Model
6%
Regression
6%
Likelihood
6%
Sampling Methods
6%
Conjugate Gradient
6%
Matrix Completion Problem
6%
Efficient Algorithms
6%
Discrete Model
6%
Smooth function
6%
Local Search Algorithm
6%
Theorem
5%
Coordinate Descent
5%
Training
5%
Condition number
5%
Engineering & Materials Science
Neural networks
100%
Polynomials
49%
Deep neural networks
38%
Factorization
32%
Chemical activation
32%
Deep learning
24%
Importance sampling
22%
Gradient methods
21%
Network layers
21%
Neurons
20%
Labels
19%
Statistics
18%
Sampling
18%
Singular value decomposition
18%
Recovery
17%
Machine learning
17%
Tensors
17%
Linear networks
16%
Convolutional neural networks
15%
Dynamical systems
14%
Gaussian distribution
12%
Mirrors
11%
Hilbert spaces
11%
Linear regression
11%
Probability distributions
11%
Bioinformatics
9%
System theory
9%
Collaborative filtering
9%
Experiments
9%
Convex optimization
9%
Costs
9%
Set theory
8%
Communication
8%
Reinforcement learning
8%
Signal processing
8%
Screening
8%
Statistical Models
7%
Composite materials
7%
Resource allocation
7%
Derivatives
7%
Trajectories
7%
Hardness
6%
Geometry
6%
Servers
6%
Decomposition
6%
Degradation
6%
Large dataset
5%
