Skip to main navigation
Skip to search
Skip to main content
Princeton University Home
Help & FAQ
Home
Profiles
Research Units
Facilities
Projects
Research output
Search by expertise, name or affiliation
Optimal learning for sequential sampling with non-parametric beliefs
Emre Barut, Warren B. Powell
Operations Research & Financial Engineering
Center for Statistics & Machine Learning
Electrical and Computer Engineering
High Meadows Environmental Institute
Research output
:
Contribution to journal
›
Article
›
peer-review
6
Scopus citations
Overview
Fingerprint
Fingerprint
Dive into the research topics of 'Optimal learning for sequential sampling with non-parametric beliefs'. Together they form a unique fingerprint.
Sort by
Weight
Alphabetically
Mathematics
Sequential Sampling
100%
Beliefs
79%
Policy
71%
Learning
66%
Kernel Estimator
42%
Weighting
37%
Ranking and Selection
26%
Kernel Estimation
24%
Predictive Distribution
23%
Correlation Structure
21%
Consistent Estimator
20%
Kernel Function
19%
Asymptotically Optimal
19%
Bandwidth
18%
Aggregation
18%
Mean square error
18%
Calculate
14%
Knowledge
14%
Gradient
14%
Unknown
11%
Estimate
8%
Business & Economics
Sampling
76%
Kernel Estimator
71%
Weighting
47%
Kernel Estimation
37%
Policy Learning
37%
Ranking and Selection
35%
Predictive Distribution
34%
Correlation Structure
30%
Kernel
29%
Bandwidth
28%
Gradient
26%
Estimator
19%
Engineering & Materials Science
Sampling
51%
Set theory
47%
Mean square error
34%
Agglomeration
31%
Bandwidth
23%