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» Machine Learning Approaches for Inducing Student Models
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ML
2002
ACM
163views Machine Learning» more  ML 2002»
13 years 8 months ago
Structural Modelling with Sparse Kernels
A widely acknowledged drawback of many statistical modelling techniques, commonly used in machine learning, is that the resulting model is extremely difficult to interpret. A numb...
Steve R. Gunn, Jaz S. Kandola
SIGIR
2000
ACM
14 years 1 months ago
Bridging the lexical chasm: statistical approaches to answer-finding
Abstract This paper investigates whether a machine can automatically learn the task of finding, within a large collection of candidate responses, the answers to questions. The lea...
Adam L. Berger, Rich Caruana, David Cohn, Dayne Fr...
ICML
2007
IEEE
14 years 9 months ago
Parameter learning for relational Bayesian networks
We present a method for parameter learning in relational Bayesian networks (RBNs). Our approach consists of compiling the RBN model into a computation graph for the likelihood fun...
Manfred Jaeger
SIGCSE
2010
ACM
186views Education» more  SIGCSE 2010»
14 years 3 months ago
Teaching operating systems using virtual appliances and distributed version control
Students learn more through hands-on project experience for computer science courses such as operating systems, but providing the infrastructure support for a large class to learn...
Oren Laadan, Jason Nieh, Nicolas Viennot
ECML
2006
Springer
14 years 16 days ago
PAC-Learning of Markov Models with Hidden State
The standard approach for learning Markov Models with Hidden State uses the Expectation-Maximization framework. While this approach had a significant impact on several practical ap...
Ricard Gavaldà, Philipp W. Keller, Joelle P...