Causal reasoning and meta learning using kernel mean embeddings

Thesis

Kernel methods have been an essential instrument in machine learning over the years due to their ability to map data into high dimensional spaces efficiently. Nowadays, especially in machine learning, multimodality in the data is a common phenomenon and hence developing tools that allow us to capture these structures is crucial. Being able to reliably represent these datasets without many distributional assumptions is at the core of the main methodology used in this thesis i.e. Kernel Mean...

Expand abstract

Authors: Ton, JF

• Type of award: DPhil
• Level of award: Doctoral
• Awarding institution: University of Oxford
• Language: English
• Keywords: meta learning; kernel methods; causal inference
• Subjects: kernel methods; causal inference; machine learning