My personal webpage has moved. You may now find Gintare Karolina Dziugaite‘s page here.

I am a member of King’s College and joined Zoubin Ghahramani’s group in Spring 2014 as a PhD student. Before that, I studied Mathematics at Warwick University and read Part III in Mathematics at Cambridge, receiving a Masters in Advanced Studies in Applied Mathematics. My PhD is funded by the EPSRC. My research interests include deep learning, generative models, and learning theory.

See my curriculum vitae for more details.

During Winter 2017, I was a long-term participant in the Foundations of Machine Learning program at the Simons Institute for the Theory of Computing at the University of Berkeley.

Research Articles

See Google scholar for a complete list.

NEW Data-dependent PAC-Bayes priors via differential privacy Gintare Karolina Dziugaite and Daniel M. Roy

Entropy-SGD optimizes the prior of a PAC-Bayes bound: Generalization properties of Entropy-SGD and data-dependent priors
Gintare Karolina Dziugaite and Daniel M. Roy
International Conference on Machine Learning (ICML) 2018.

Computing Nonvacuous Generalization Bounds for Deep (Stochastic) Neural Networks with Many More Parameters than Training Data Gintare Karolina Dziugaite and Daniel M. Roy
Uncertainty in Artificial Intelligence (UAI) 2017.

A study of the effect of JPG compression on adversarial images
Gintare Karolina Dziugaite, Zoubin Ghahramani, and Daniel M. Roy

Neural Network Matrix Factorization Gintare Karolina Dziugaite, Daniel M. Roy, and Zoubin Ghahramani

Training generative neural networks via Maximum Mean Discrepancy optimization Gintare Karolina Dziugaite, Daniel M. Roy, and Zoubin Ghahramani
Uncertainty in Artificial Intelligence (UAI) 2015.