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» Learning with Idealized Kernels
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BMCBI
2010
118views more  BMCBI 2010»
14 years 10 months ago
Walk-weighted subsequence kernels for protein-protein interaction extraction
Background: The construction of interaction networks between proteins is central to understanding the underlying biological processes. However, since many useful relations are exc...
Seonho Kim, Juntae Yoon, Jihoon Yang, Seog Park
NIPS
2008
14 years 11 months ago
Structure Learning in Human Sequential Decision-Making
We use graphical models and structure learning to explore how people learn policies in sequential decision making tasks. Studies of sequential decision-making in humans frequently...
Daniel Acuña, Paul R. Schrater
WWW
2007
ACM
15 years 10 months ago
Web page classification with heterogeneous data fusion
Web pages are more than text and they contain much contextual and structural information, e.g., the title, the meta data, the anchor text, etc., each of which can be seen as a dat...
Zenglin Xu, Irwin King, Michael R. Lyu
ALT
2004
Springer
15 years 7 months ago
Relative Loss Bounds and Polynomial-Time Predictions for the k-lms-net Algorithm
We consider a two-layer network algorithm. The first layer consists of an uncountable number of linear units. Each linear unit is an LMS algorithm whose inputs are first “kerne...
Mark Herbster
COLT
1999
Springer
15 years 2 months ago
Covering Numbers for Support Vector Machines
—Support vector (SV) machines are linear classifiers that use the maximum margin hyperplane in a feature space defined by a kernel function. Until recently, the only bounds on th...
Ying Guo, Peter L. Bartlett, John Shawe-Taylor, Ro...