The University of Southampton

Steven Squires 

PhD Student

Steven Squires has a 1st Class MPhys degree in Physics from the University of Manchester and an MSc with distinction in Computer Science from the University of Southampton. He started a PhD in Machine Learning at the University of Southampton in 2015 under the supervision of Professor Mahesan Niranjan and Professor Adam Prügel-Bennett.


Research interests

My main research interests are in the fields of non-negative matrix factorisation (NMF) and neural networks. NMF is primarily a dimensionality reduction technique which is crucial in reducing the complexity of high-dimensional data. NMF has the additional benefit of tending to, naturally, lead to a sparse and parts based representation of the data, which may be significantly more interpretable than more holistic approaches such as principal component analysis. Neural networks in various forms have, in recent years, considerably improved upon the state of the art in various machine learning fields. These modern neural networks can produce excellent results but not the reasoning behind them. Improving the interpretabiliy of neural networks may lead us to produce better systems in the future and be able to trust the results provided.


Squires, Steven, Prugel-Bennett, Adam and Niranjan, Mahesan (2017) Rank selection in non-negative matrix factorization using minimum description Length. Neural Computation, 29 (8), 2164-2176. (doi:10.1162/NECO_a_00980).

Squires, Steven, Edward, Montesdeoca Bermudez, Luis, Jairo, Prugel-Bennett, Adam and Niranjan, Mahesan (2017) Non-negative matrix factorization with exogenous inputs for modeling financial data. In Lecture Notes in Computer Science. vol. 10635, Springer. pp. 873-881 . (doi:10.1007/978-3-319-70096-0_89).

Squires, Steven, Edward, Ewing, Robert, Prugel-Bennett, Adam and Niranjan, Mahesan (2017) A method of integrating spatial proteomics and protein-protein interaction network data. In Lecture Notes in Computer Science. Springer. 9 pp . (doi:10.1007/978-3-319-70139-4_79).


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