Testing and learning on distributional and set inputs
<p>As machine learning gains significant attention in many disciplines and research communities, the variety of data structures has increased, with examples including distributions and sets of observations. In this thesis, we consider sets and distributions as inputs for machine learning pr...
Автор: | Law, H |
---|---|
Інші автори: | Sejdinovic, D |
Формат: | Дисертація |
Мова: | English |
Опубліковано: |
2019
|
Предмети: |
Схожі ресурси
Схожі ресурси
-
Utilizing Statistical Tests for Comparing Machine Learning Algorithms
за авторством: Hozan Khalid Hamarashid
Опубліковано: (2021-07-01) -
The information of attribute uncertainties: what convolutional neural networks can learn about errors in input data
за авторством: Natália V N Rodrigues, та інші
Опубліковано: (2023-01-01) -
Towards trustworthy machine learning with kernels
за авторством: Chau, SL
Опубліковано: (2023) -
Towards data-efficient deep learning with meta-learning and symmetries
за авторством: Xu, J
Опубліковано: (2023) -
Kernel-based hypothesis tests: large-scale approximations and Bayesian perspectives
за авторством: Zhang, Q
Опубліковано: (2019)