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Spring Talks

Spring 2011 May 3 – Combining structured predictions from multiple “experts” without any supervised data (Alex Klementiev) Apr 26 – Rare class prediction (Juri Ganitkevitch) Apr 19 – Hyperparameter estimation in Dirichlet process mixture models (Nicholas Andrews) Apr 12 – Dirichlet processes and DP mixture models (Adam Teichert) Weekly Tip: Ever wanted an exceptionally high-quality, […]

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Machine Learning Tea

The Johns Hopkins Machine Learning Tea is an informal gathering of students and postdocs interested in machine learning, statistics, and their applications. We meet every week while class is in session. If you’re interested in attending, please sign up for the [ Google group] for announcements and discussion. [ Snacks] and, of course, tea will […]

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