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CIKM
2009
Springer
15 years 4 months ago
An empirical study on using hidden markov model for search interface segmentation
This paper describes a hidden Markov model (HMM) based approach to perform search interface segmentation. Automatic processing of an interface is a must to access the invisible co...
Ritu Khare, Yuan An
100
Voted
UAI
2000
15 years 1 months ago
Gaussian Process Networks
In this paper we address the problem of learning the structure of a Bayesian network in domains with continuous variables. This task requires a procedure for comparing different c...
Nir Friedman, Iftach Nachman
93
Voted
ECCV
2008
Springer
16 years 1 months ago
Learning Optical Flow
Assumptions of brightness constancy and spatial smoothness underlie most optical flow estimation methods. In contrast to standard heuristic formulations, we learn a statistical mod...
Deqing Sun, Stefan Roth, J. P. Lewis, Michael J. B...
ICASSP
2011
IEEE
14 years 3 months ago
Belief theoretic methods for soft and hard data fusion
In many contexts, one is confronted with the problem of extracting information from large amounts of different types soft data (e.g., text) and hard data (from e.g., physics-based...
Thanuka Wickramarathne, Kamal Premaratne, Manohar ...
BMCBI
2008
179views more  BMCBI 2008»
14 years 11 months ago
Bayesian modeling of recombination events in bacterial populations
Background: We consider the discovery of recombinant segments jointly with their origins within multilocus DNA sequences from bacteria representing heterogeneous populations of fa...
Pekka Marttinen, Adam Baldwin, William P. Hanage, ...