Skip to main navigation
Skip to search
Skip to main content
Princeton University Home
Help & FAQ
Home
Profiles
Research units
Facilities
Projects
Research output
Press/Media
Search by expertise, name or affiliation
Learning Convex Optimization Control Policies
Akshay Agrawal
, Shane Barratt
, Stephen Boyd
,
Bartolomeo Stellato
Operations Research & Financial Engineering
Research output
:
Contribution to journal
›
Conference article
›
peer-review
51
Scopus citations
Overview
Fingerprint
Fingerprint
Dive into the research topics of 'Learning Convex Optimization Control Policies'. Together they form a unique fingerprint.
Sort by
Weight
Alphabetically
Keyphrases
Convex Optimization
100%
Control Policy
100%
Optimization Control
100%
Linear Quadratic Regulator
50%
Gradient Approximation
25%
Performance Metrics
25%
Optimization Problem
25%
Convex Programming
25%
Approximate Dynamic Programming
25%
Convex Optimization Problem
25%
Control Types
25%
Model Predictive Control
25%
Grid Search
25%
Convex Model
25%
Computer Science
Convex Optimization
100%
Optimization Problem
66%
Performance Metric
33%
And-States
33%
Good Performance
33%
Dynamic Programming
33%
Predictive Model
33%
Mathematics
Approximates
100%
Convex Programming
50%
Predictive Model
50%
Grid Search
50%
Engineering
Convex Model
25%