I am a final year PhD student at the Oxford-Warwick Statistics Programme (OxWaSP), working under the joint supervision of Professor Yee Whye Teh (Oxford), Dr. Dario Spanò (Warwick) and Dr. Paul Jenkins (Warwick). I am also part of the Oxford statistical machine learning group (OxCSML).
My research interests lie in the fields of Bayesian machine learning and deep learning. In particular, I am interested in developing algorithms for large-scale machine learning and Bayesian nonparametric models with realistic dependency structures. I have applied my work to topic modelling, recommender systems and population genetics.
- V. Perrone, P. A. Jenkins, D. Spano, Y. W. Teh. Poisson Random Fields for Dynamic Feature Models. Journal of Machine Learning Research (JMLR). 2017. [pdf] [arXiv] [data]
- V. Perrone, R. Jenatton, M. Seeger, C. Archambeau. Multiple Adaptive Bayesian Linear Regression for Scalable Bayesian Optimization with Warm Start. NIPS 2017 Workshop on Meta-Learning. Selected for contributed talk. 2017. [pdf] [arXiv] [workshop link]
- J. Chan, V. Perrone, J. Spence, P. A. Jenkins, S. Mathieson and Yun S. Song. A Likelihood-Free Inference Framework for Population Genetic Data using Exchangeable Neural Networks. NIPS 2017 Workshop on Machine Learning in Computational Biology. 2017. [arXiv] [bioRxiv] [workshop link]
- X. Lu*, V. Perrone*, L. Hasenclever, Y. W. Teh, S. J. Vollmer. Relativistic Monte Carlo. Proceedings of the 20th International Conference on Artificial Intelligence and Statistics (AISTATS). 2017. [pdf] [arXiv] [code] [video] *joint first author
Selected Talks & Posters
- 9 Dec 2017: Contributed Talk and Poster. Workshop on Meta-Learning, NIPS 2017 (Long Beach, US)
- 9 Dec 2017: Poster. Workshop on Machine Learning in Computational Biology, NIPS 2017 (Long Beach, US)
- 27 Jun 2017: Poster. 11th Conference on Bayesian Nonparametrics, BNP11 [Poster Award winner] (Paris, France)
- 20 Apr 2017: Poster. 20th Conference on Artificial Intelligence and Statistics, AISTATS 2017 (Fort Lauderdale, US)
- 10 Dec 2016: Contributed Talk and Poster. Bayesian Deep Learning workshop, NIPS 2016 (Barcelona, Spain)