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Committee Date Time Place Paper Title / Authors Abstract Paper #
IBISML 2013-11-13
15:45		 Tokyo Tokyo Institute of Technology, Kuramae-Kaikan [Poster Presentation] Learning Common Features of Parametrized Tasks
Ichiro Takeuchi, Tatsuya Hongo (Nagoya Inst. of Tech.), Masashi Sugiyama (Tokyo Inst. of Tech.), Shinichi Nakajima (Nikon) IBISML2013-66		 We introduce a novel formulation of multi-task learning (MTL) called parametric task learning (PTL) that can systematica... [more] IBISML2013-66
pp.225-232
IBISML 2010-11-04
15:00		 Tokyo IIS, Univ. of Tokyo [Poster Presentation] A Study on Simultaneous Feature Selection for Cost-Sensitive Classifiers Using Mixed-Norm Regularization
Toru Sugiura, Kazuaki Koide, Tatsuya Hongo, Masayuki Karasuyama, Ichiro Takeuchi (NIT) IBISML2010-70		 Cost-sensitive learning is useful for binary classification when the
costs of miss-classifications are not symmetric. I... [more]		 IBISML2010-70
pp.83-90
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