Thesis icon

Thesis

Large scale methods for kernels, causal inference and survival modelling

Abstract:

Machine Learning is widely applied in industrial applications such as product design and recommendations, sales and churn prediction among many others. This thesis proposes scalable methods geared towards industrial application where we address problems related to dimensionality, uncertainty quantification and inference.

First, we inferring features from images of products that are pertinent to high sales. We propose an additional regularization objective inspired by kernel two-sam...

Expand abstract

Actions


Access Document


Files:

Authors


More by this author
Division:
MPLS
Department:
Statistics
Role:
Author

Contributors

Role:
Supervisor
ORCID:
0000-0001-5547-9213
Role:
Supervisor
ORCID:
0000-0002-9341-1313
Role:
Examiner
Type of award:
DPhil
Level of award:
Doctoral
Awarding institution:
University of Oxford
DOI:
Language:
English
Keywords:
Subjects:
Deposit date:
2023-02-05

Terms of use


Views and Downloads






If you are the owner of this record, you can report an update to it here: Report update to this record

TO TOP