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» Automatic Ordering of Subgoals - A Machine Learning Approach
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127
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EMNLP
2008
15 years 5 months ago
Learning with Probabilistic Features for Improved Pipeline Models
We present a novel learning framework for pipeline models aimed at improving the communication between consecutive stages in a pipeline. Our method exploits the confidence scores ...
Razvan C. Bunescu
124
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ICML
2010
IEEE
15 years 4 months ago
Learning Markov Logic Networks Using Structural Motifs
Markov logic networks (MLNs) use firstorder formulas to define features of Markov networks. Current MLN structure learners can only learn short clauses (4-5 literals) due to extre...
Stanley Kok, Pedro Domingos
118
Voted
AAAI
2008
15 years 6 months ago
Exposing Parameters of a Trained Dynamic Model for Interactive Music Creation
As machine learning (ML) systems emerge in end-user applications, learning algorithms and classifiers will need to be robust to an increasingly unpredictable operating environment...
Dan Morris, Ian Simon, Sumit Basu
119
Voted
COLT
2005
Springer
15 years 9 months ago
A PAC-Style Model for Learning from Labeled and Unlabeled Data
Abstract. There has been growing interest in practice in using unlabeled data together with labeled data in machine learning, and a number of different approaches have been develo...
Maria-Florina Balcan, Avrim Blum
97
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DSMML
2004
Springer
15 years 9 months ago
Multi Channel Sequence Processing
Abstract. This paper summarizes some of the current research challenges arising from multi-channel sequence processing. Indeed, multiple real life applications involve simultaneous...
Samy Bengio, Hervé Bourlard