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CORR
2012
Springer
187views Education» more  CORR 2012»
13 years 7 months ago
Sequential Inference for Latent Force Models
Latent force models (LFMs) are hybrid models combining mechanistic principles with non-parametric components. In this article, we shall show how LFMs can be equivalently formulate...
Jouni Hartikainen, Simo Särkkä
KDD
2006
ACM
147views Data Mining» more  KDD 2006»
16 years 1 days ago
Summarizing itemset patterns using probabilistic models
In this paper, we propose a novel probabilistic approach to summarize frequent itemset patterns. Such techniques are useful for summarization, post-processing, and end-user interp...
Chao Wang, Srinivasan Parthasarathy
NECO
2002
104views more  NECO 2002»
14 years 11 months ago
An Unsupervised Ensemble Learning Method for Nonlinear Dynamic State-Space Models
A Bayesian ensemble learning method is introduced for unsupervised extraction of dynamic processes from noisy data. The data are assumed to be generated by an unknown nonlinear ma...
Harri Valpola, Juha Karhunen
AIRS
2010
Springer
14 years 9 months ago
Event Recognition from News Webpages through Latent Ingredients Extraction
We investigate the novel problem of event recognition from news webpages. "Events" are basic text units containing news elements. We observe that a news article is always...
Rui Yan, Yu Li, Yan Zhang, Xiaoming Li
ICMCS
2005
IEEE
169views Multimedia» more  ICMCS 2005»
15 years 5 months ago
Dynamic language model adaptation using latent topical information and automatic transcripts
This paper considers dynamic language model adaptation for Mandarin broadcast news recognition. Both contemporary newswire texts and in-domain automatic transcripts were exploited...
Berlin Chen