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ECIR
2009
Springer
14 years 4 months ago
A Comparative Study of Utilizing Topic Models for Information Retrieval
We explore the utility of different types of topic models for retrieval purposes. Based on prior work, we describe several ways that topic models can be integrated into the retrie...
Xing Yi, James Allan
JMLR
2010
192views more  JMLR 2010»
13 years 2 months ago
Efficient Learning of Deep Boltzmann Machines
We present a new approximate inference algorithm for Deep Boltzmann Machines (DBM's), a generative model with many layers of hidden variables. The algorithm learns a separate...
Ruslan Salakhutdinov, Hugo Larochelle
SIGMOD
2008
ACM
162views Database» more  SIGMOD 2008»
14 years 7 months ago
Event queries on correlated probabilistic streams
A major problem in detecting events in streams of data is that the data can be imprecise (e.g. RFID data). However, current state-ofthe-art event detection systems such as Cayuga ...
Christopher Ré, Dan Suciu, Julie Letchner, ...
ICRA
2006
IEEE
149views Robotics» more  ICRA 2006»
14 years 1 months ago
On Learning the Statistical Representation of a Task and Generalizing it to Various Contexts
— This paper presents an architecture for solving generically the problem of extracting the constraints of a given task in a programming by demonstration framework and the problem...
Sylvain Calinon, Florent Guenter, Aude Billard
CORR
2010
Springer
69views Education» more  CORR 2010»
13 years 7 months ago
Epistemic irrelevance in credal nets: the case of imprecise Markov trees
We focus on credal nets, which are graphical models that generalise Bayesian nets to imprecise probability. We replace the notion of strong independence commonly used in credal ne...
Gert de Cooman, Filip Hermans, Alessandro Antonucc...