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MLG
2007
Springer
16 years 22 days ago
Abductive Stochastic Logic Programs for Metabolic Network Inhibition Learning
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, Jose Santos
ICALT
2006
IEEE
16 years 19 days ago
Vicarious Learning and Multimodal Dialogue
Vicarious Learning is learning from watching others learn. We believe that this is a powerful model for computer-based learning. Learning episodes can be captured and replayed to ...
John Lee
ECML
1993
Springer
15 years 10 months ago
Complexity Dimensions and Learnability
In machine learning theory, problem classes are distinguished because of di erences in complexity. In 6 , a stochastic model of learning from examples was introduced. This PAClear...
Shan-Hwei Nienhuys-Cheng, Mark Polman
ICML
2010
IEEE
15 years 7 months ago
Deep Supervised t-Distributed Embedding
Deep learning has been successfully applied to perform non-linear embedding. In this paper, we present supervised embedding techniques that use a deep network to collapse classes....
Martin Renqiang Min, Laurens van der Maaten, Zinen...
ICMLA
2009
15 years 4 months ago
Structured Prediction Models for Chord Transcription of Music Audio
Chord sequences are a compact and useful description of music, representing each beat or measure in terms of a likely distribution over individual notes without specifying the not...
Adrian Weller, Daniel P. W. Ellis, Tony Jebara