Skip to main navigation
Skip to search
Skip to main content
Northwestern Scholars Home
Help & FAQ
Home
Experts
Organizations
Research Output
Grants
Core Facilities
Datasets
Search by expertise, name or affiliation
Models and algorithms for distributionally robust least squares problems
Sanjay Mehrotra
*
, He Zhang
*
Corresponding author for this work
Industrial Engineering and Management Sciences
Research output
:
Contribution to journal
›
Article
›
peer-review
23
Scopus citations
Overview
Fingerprint
Fingerprint
Dive into the research topics of 'Models and algorithms for distributionally robust least squares problems'. Together they form a unique fingerprint.
Sort by
Weight
Alphabetically
INIS
probability
100%
programming
80%
optimization
40%
algorithms
40%
least square fit
40%
data
20%
constraints
20%
distance
20%
density
20%
stochastic processes
20%
lagrangian
20%
probabilistic estimation
20%
approximations
20%
polynomials
20%
cones
20%
Mathematics
Probability Measure
60%
Bounds
60%
Measures
60%
Least Square
40%
Finite Support
40%
Optimization
20%
Programming Problem
20%
Sample Average
20%
Lagrangian
20%
Density Function
20%
Kantorovich
20%
Confidence Region
20%
Algorithm
20%
Constraints
20%
Approximation
20%
Order
20%
Computer Science
Probability Measure
60%
Finite Support
40%
Semidefinite Programming
40%
References
40%
Probability
40%
Optimization Problem
20%
Optimization
20%
Polynomial Time Algorithm
20%
Density Function
20%
Simulation Mode
20%
Stochastic Programming
20%