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» Probabilistic-Logic Models: Reasoning and Learning with Rela...
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PAMI
2011
14 years 4 months ago
Greedy Learning of Binary Latent Trees
—Inferring latent structures from observations helps to model and possibly also understand underlying data generating processes. A rich class of latent structures are the latent ...
Stefan Harmeling, Christopher K. I. Williams
ALIFE
2010
14 years 8 months ago
Modeling Social Learning of Language and Skills
We present a model of social learning of both language and skills, while assuming—insofar as possible—strict autonomy, virtual embodiment, and situatedness. This model is built...
Paul Vogt, Evert Haasdijk
NIPS
1998
14 years 11 months ago
Approximate Learning of Dynamic Models
Inference is a key component in learning probabilistic models from partially observable data. When learning temporal models, each of the many inference phases requires a complete ...
Xavier Boyen, Daphne Koller
ICML
2008
IEEE
15 years 10 months ago
Training structural SVMs when exact inference is intractable
While discriminative training (e.g., CRF, structural SVM) holds much promise for machine translation, image segmentation, and clustering, the complex inference these applications ...
Thomas Finley, Thorsten Joachims
EMNLP
2008
14 years 11 months ago
Unsupervised Multilingual Learning for POS Tagging
We demonstrate the effectiveness of multilingual learning for unsupervised part-of-speech tagging. The key hypothesis of multilingual learning is that by combining cues from multi...
Benjamin Snyder, Tahira Naseem, Jacob Eisenstein, ...