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» Machine Learning Approaches for Inducing Student Models
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ML
2002
ACM
163views Machine Learning» more  ML 2002»
15 years 3 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
15 years 7 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
16 years 4 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»
15 years 10 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
15 years 7 months 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...