Tomi SILANDER | Naver Labs Europe
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Machine Learning and Optimization

I'm a senior research scientist at NAVER LABS Europe (NLE).

Author of B-course, the first Bayesian network learning tool online, I did my PhD at Helsinki University.

I am probably best known for developing exact structure learning methods with which I've studied the problems in the BDeu model selection criterion.

I've also worked on developing alternative, information theoretic model selection criteria for structure learning such as the factorized normalized maximum likelihood criterion (fNML) and the quotient normalized maximum likelihood criterion (qNML).

I've worked in both academic and industrial research centres (University of Helsinki, the National University of Singapore, Nokia Research Centre, A-Star Institute of High Performance Computing, and Xerox Research Centre Europe).

I'm an active reviewer for many machine learning conferences and journals.