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ICDM
2008
IEEE
150views Data Mining» more  ICDM 2008»
15 years 11 months ago
Pseudolikelihood EM for Within-network Relational Learning
In this work, we study the problem of within-network relational learning and inference, where models are learned on a partially labeled relational dataset and then are applied to ...
Rongjing Xiang, Jennifer Neville
ICDM
2008
IEEE
182views Data Mining» more  ICDM 2008»
15 years 11 months ago
Multiple-Instance Regression with Structured Data
We present a multiple-instance regression algorithm that models internal bag structure to identify the items most relevant to the bag labels. Multiple-instance regression (MIR) op...
Kiri L. Wagstaff, Terran Lane, Alex Roper
JMLR
2002
106views more  JMLR 2002»
15 years 4 months ago
Some Greedy Learning Algorithms for Sparse Regression and Classification with Mercer Kernels
We present some greedy learning algorithms for building sparse nonlinear regression and classification models from observational data using Mercer kernels. Our objective is to dev...
Prasanth B. Nair, Arindam Choudhury 0002, Andy J. ...
FUZZIEEE
2007
IEEE
15 years 11 months ago
Learning Undirected Possibilistic Networks with Conditional Independence Tests
—Approaches based on conditional independence tests are among the most popular methods for learning graphical models from data. Due to the predominance of Bayesian networks in th...
Christian Borgelt
AIED
2009
Springer
15 years 11 months ago
Using Learning Decomposition to Analyze Instructional Effectiveness in the ASSISTment System
A basic question of instruction is how effective it is in promoting student learning. This paper presents a study determining the relative efficacy of different instructional conte...
Mingyu Feng, Neil T. Heffernan, Joseph E. Beck