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ICDM
2009
IEEE
92views Data Mining» more  ICDM 2009»
14 years 11 months ago
Semi-supervised Multi-task Learning with Task Regularizations
Multi-task learning refers to the learning problem of performing inference by jointly considering multiple related tasks. There have already been many research efforts on supervise...
Fei Wang, Xin Wang, Tao Li
ICALT
2003
IEEE
15 years 6 months ago
Students' Understanding of Computer Networks in an Internationally Distributed Course
The different ways in which concepts within computer networks are understood by master level students who take an internationally distributed project-based course have been identi...
Anders Berglund, Arnold Neville Pears
NIPS
2001
15 years 2 months ago
Algorithmic Luckiness
Classical statistical learning theory studies the generalisation performance of machine learning algorithms rather indirectly. One of the main detours is that algorithms are studi...
Ralf Herbrich, Robert C. Williamson
SDM
2011
SIAM
233views Data Mining» more  SDM 2011»
14 years 4 months ago
Multi-Instance Mixture Models
Multi-instance (MI) learning is a variant of supervised learning where labeled examples consist of bags (i.e. multi-sets) of feature vectors instead of just a single feature vecto...
James R. Foulds, Padhraic Smyth
ICDM
2009
IEEE
169views Data Mining» more  ICDM 2009»
14 years 11 months ago
Learning the Shared Subspace for Multi-task Clustering and Transductive Transfer Classification
There are many clustering tasks which are closely related in the real world, e.g. clustering the web pages of different universities. However, existing clustering approaches neglec...
Quanquan Gu, Jie Zhou