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Frank Jäkel

 

Wednesday 8th October 2014

Time: 4pm

 

Basement Seminar Room

Alexandra House, 17 Queen Square, London, WC1N 3AR

 

Categorization: From Psychology to Machine Learning and Back

 

 

Categorization is a fundamental cognitive ability. Many, if not all, so-called higher cognitive functions, like language or problem-solving, crucially depend on categorization. Correspondingly, categorization plays a central role in cognitive science and artificial intelligence. Early machine learning algorithms for categorization were inspired by
psychology and neuroscience. However, today machine learning is a mature field and more recent methods are usually seen to be grounded in statistics rather than in cognitive science. Kernel methods, in particular, have gained popularity in machine learning and have proved
to be successful in many applied categorization problems. I will describe how similar ideas have developed in psychology and how insights from machine learning could feed back into cognitive science.

 

1998-2001 Studies in Cognitive Science at Universität Osnabrück
2000-2001 Semester abroad at the University of Edinburgh
2001-2003 Studies in Neural and Behavioural Sciences at Universität
Tübingen
2004-2007 Doctoral student at MPI for Biological Cybernetics (Department
of Empirical Inference)
2007-2008 Postdoctoral fellow at TU Berlin (Modelling of Cognitive
Processes)
2008-2010 Postdoctoral fellow at MIT (Computational Cognitive Science)
Since autumn 2010 Juniorprofessor for Cognitive Modeling