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ML
2008
ACM
150views Machine Learning» more  ML 2008»
15 years 6 months ago
Learning probabilistic logic models from probabilistic examples
Abstract. We revisit an application developed originally using Inductive Logic Programming (ILP) by replacing the underlying Logic Program (LP) description with Stochastic Logic Pr...
Jianzhong Chen, Stephen Muggleton, José Car...
HUC
2010
Springer
15 years 5 months ago
Routine as resource for the design of learning systems
Even though the coordination of kids’ activities is largely successful, the modern dual income family still regularly experiences breakdowns in their practices. Families often r...
Scott Davidoff
NECO
2010
136views more  NECO 2010»
15 years 5 months ago
Learning to Represent Spatial Transformations with Factored Higher-Order Boltzmann Machines
To allow the hidden units of a restricted Boltzmann machine to model the transformation between two successive images, Memisevic and Hinton (2007) introduced three-way multiplicat...
Roland Memisevic, Geoffrey E. Hinton
CIKM
2010
Springer
15 years 4 months ago
Combining link and content for collective active learning
In this paper, we study a novel problem Collective Active Learning, in which we aim to select a batch set of "informative" instances from a networking data set to query ...
Lixin Shi, Yuhang Zhao, Jie Tang
CVPR
2009
IEEE
1390views Computer Vision» more  CVPR 2009»
17 years 1 months ago
Stacks of Convolutional Restricted Boltzmann Machines for Shift-Invariant Feature Learning
In this paper we present a method for learning classspecific features for recognition. Recently a greedy layerwise procedure was proposed to initialize weights of deep belief ne...
Mohammad Norouzi (Simon Fraser University), Mani R...