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17 years 4 months ago
Gaussian Processes for Machine Learning
"Gaussian processes (GPs) provide a principled, practical, probabilistic approach to learning in kernel machines. GPs have received increased attention in the machine-learning...
Carl Edward Rasmussen and Christopher K. I. Willia...
ITCC
2003
IEEE
15 years 11 months ago
A Learning Objects Approach to Teaching Programming
The goal of this paper is to describe a new approach to a content creation and delivery mechanism for a programming course. This approach is based on the concept of creating a lar...
Victor Adamchik, Ananda Gunawardena
IEEEPACT
2008
IEEE
16 years 28 days ago
Feature selection and policy optimization for distributed instruction placement using reinforcement learning
Communication overheads are one of the fundamental challenges in a multiprocessor system. As the number of processors on a chip increases, communication overheads and the distribu...
Katherine E. Coons, Behnam Robatmili, Matthew E. T...
KDD
2012
ACM
188views Data Mining» more  KDD 2012»
13 years 9 months ago
A probabilistic model for multimodal hash function learning
In recent years, both hashing-based similarity search and multimodal similarity search have aroused much research interest in the data mining and other communities. While hashing-...
Yi Zhen, Dit-Yan Yeung
146
Voted
AIED
2009
Springer
16 years 1 months ago
Scaffolding Motivation and Metacognition in Learning Programming
This paper explores the role that feedback based on past actions and motivational states of the learner can have in a motivationally and metacognitively aware Intelligent Tutoring ...
Alison Hull, Benedict du Boulay