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ICASSP
2008
IEEE
14 years 1 months ago
Bayesian update of dialogue state for robust dialogue systems
This paper presents a new framework for accumulating beliefs in spoken dialogue systems. The technique is based on updating a Bayesian Network that represents the underlying state...
Blaise Thomson, Jost Schatzmann, Steve Young
WSDM
2012
ACM
301views Data Mining» more  WSDM 2012»
12 years 2 months ago
Learning evolving and emerging topics in social media: a dynamic nmf approach with temporal regularization
As massive repositories of real-time human commentary, social media platforms have arguably evolved far beyond passive facilitation of online social interactions. Rapid analysis o...
Ankan Saha, Vikas Sindhwani
COLT
1999
Springer
13 years 11 months ago
Regret Bounds for Prediction Problems
We present a unified framework for reasoning about worst-case regret bounds for learning algorithms. This framework is based on the theory of duality of convex functions. It brin...
Geoffrey J. Gordon
KDD
2009
ACM
192views Data Mining» more  KDD 2009»
14 years 7 months ago
Learning optimal ranking with tensor factorization for tag recommendation
Tag recommendation is the task of predicting a personalized list of tags for a user given an item. This is important for many websites with tagging capabilities like last.fm or de...
Steffen Rendle, Leandro Balby Marinho, Alexandros ...
CIKM
2010
Springer
13 years 5 months ago
Rank learning for factoid question answering with linguistic and semantic constraints
This work presents a general rank-learning framework for passage ranking within Question Answering (QA) systems using linguistic and semantic features. The framework enables query...
Matthew W. Bilotti, Jonathan L. Elsas, Jaime G. Ca...