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KDD
2010
ACM
245views Data Mining» more  KDD 2010»
13 years 11 months ago
Learning incoherent sparse and low-rank patterns from multiple tasks
We consider the problem of learning incoherent sparse and lowrank patterns from multiple tasks. Our approach is based on a linear multi-task learning formulation, in which the spa...
Jianhui Chen, Ji Liu, Jieping Ye
ICML
2009
IEEE
14 years 3 months ago
Learning linear dynamical systems without sequence information
Virtually all methods of learning dynamic systems from data start from the same basic assumption: that the learning algorithm will be provided with a sequence, or trajectory, of d...
Tzu-Kuo Huang, Jeff Schneider
BMCBI
2008
228views more  BMCBI 2008»
13 years 9 months ago
Adaptive diffusion kernel learning from biological networks for protein function prediction
Background: Machine-learning tools have gained considerable attention during the last few years for analyzing biological networks for protein function prediction. Kernel methods a...
Liang Sun, Shuiwang Ji, Jieping Ye
EDM
2010
154views Data Mining» more  EDM 2010»
13 years 7 months ago
Can We Get Better Assessment From A Tutoring System Compared to Traditional Paper Testing? Can We Have Our Cake (Better Assessme
Dynamic assessment (DA) has been advocated as an interactive approach to conduct assessments to students in the learning systems as it can differentiate student proficiency at a fi...
Mingyu Feng, Neil T. Heffernan
KDD
2012
ACM
201views Data Mining» more  KDD 2012»
11 years 11 months ago
Learning from crowds in the presence of schools of thought
Crowdsourcing has recently become popular among machine learning researchers and social scientists as an effective way to collect large-scale experimental data from distributed w...
Yuandong Tian, Jun Zhu