Adrian Goldwaser


About Me

I am a PhD student at Cambridge University supervised by Hong Ge in the Machine Learning Group, supported by the Harding Distinguished Postgraduate Scholars Programme. I am interested in neural network theory, specifically in understanding the inductive biases and using them to explain generalisation and other empirical phenomena that we observe. I am also interested in approaches that improve the robustness and safety of deep learning methods and AI in general.

My honours thesis was supervised by Michael Thielscher and Alan Blair and before that I completed research placements with Andreas Schutt and Haris Aziz.

Publications

Learning Deep Neural Networks by Iterative Linearisation
Adrian Goldwaser and Hong Ge
Optimization for Machine Learning (OPT-ML) at Neurips 2022
[pdf] [bib] [doi] [arxiv]
Deep Reinforcement Learning for General Game Playing
Adrian Goldwaser and Michael Thielscher
AAAI 2020 (oral presentation)
[pdf] [bib] [doi]
Optimal Torpedo Scheduling
Adrian Goldwaser and Andreas Schutt
JAIR 2018
[pdf] [bib] [doi]
Optimal Torpedo Scheduling
Adrian Goldwaser and Andreas Schutt
CP 2017 - named Best Student Paper
[pdf] [bib] [doi]
Coalitional Exchange Stable Matchings in Marriage and Roommate Markets
Haris Aziz and Adrian Goldwaser
AAMAS 2017 (extended abstract)
[pdf] [bib] [doi]
Priority Search with MiniZinc
Thibaut Feydy, Adrian Goldwaser, Andreas Schutt, Peter J. Stuckey and Kenneth D. Young.
ModRef 2017
[pdf] [bib]

Teaching

Personal

I have been juggling since 2006, you can see some projects related to that here.