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CORR
2012
Springer
210views Education» more  CORR 2012»
12 years 4 months ago
Fast MCMC sampling for Markov jump processes and continuous time Bayesian networks
Markov jump processes and continuous time Bayesian networks are important classes of continuous time dynamical systems. In this paper, we tackle the problem of inferring unobserve...
Vinayak Rao, Yee Whye Teh
ACL
2009
13 years 6 months ago
Bayesian Unsupervised Word Segmentation with Nested Pitman-Yor Language Modeling
In this paper, we propose a new Bayesian model for fully unsupervised word segmentation and an efficient blocked Gibbs sampler combined with dynamic programming for inference. Our...
Daichi Mochihashi, Takeshi Yamada, Naonori Ueda
JMLR
2010
149views more  JMLR 2010»
13 years 3 months ago
Learning Bayesian Network Structure using LP Relaxations
We propose to solve the combinatorial problem of finding the highest scoring Bayesian network structure from data. This structure learning problem can be viewed as an inference pr...
Tommi Jaakkola, David Sontag, Amir Globerson, Mari...
CIMCA
2008
IEEE
14 years 3 months ago
Tree Exploration for Bayesian RL Exploration
Research in reinforcement learning has produced algorithms for optimal decision making under uncertainty that fall within two main types. The first employs a Bayesian framework, ...
Christos Dimitrakakis
TSD
2010
Springer
13 years 6 months ago
Hybrid HMM/BLSTM-RNN for Robust Speech Recognition
The question how to integrate information from different sources in speech decoding is still only partially solved (layered architecture versus integrated search). We investigate t...
Yang Sun, Louis ten Bosch, Lou Boves