Yu Wang

  • University of Cambridge
  • Postdoc Research Associate. Department of Pure Math and Statistics, University of Cambridge.

My research interests

  • I completed my PhD recently at Computer Science Department, University of Cambridge. My PhD research focuses on statistical machine learning and variational Bayesian Learning. Specifically, I develop efficient statistical Bayesian models for pattern clustering and patter recognition tasks and I investigate the associate underlying optimization mechanism which drives the model towards successful inference and regression. My research also pays emphasis on sparsity driven machine learning phenomenon. My resent research successfully derives the closed form sparsity driven cost function hidden behind the hierarchical statistical clustering techniques (see my recent paper on ICML 2015 and UAI 2015).
  • Generally, my research interest include Machine Learning, Bayesian Learning, Sparsity Learning, Learning Theory, Optimization, and Duality Analysis. More specifically, I am interested in applying efficient learning algorithms to the problem of computer vision and medical images.

People I collaborate with

I’m currently working on 2 CMIH projects

Unsupervised Brain tumor and abnormality detection

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Computer-aided detection and personalised screening in breast imaging

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Key Publications