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» Learning Generative Models with the Up-Propagation Algorithm
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ACL
2003
13 years 9 months ago
Probabilistic Text Structuring: Experiments with Sentence Ordering
Ordering information is a critical task for natural language generation applications. In this paper we propose an approach to information ordering that is particularly suited for ...
Mirella Lapata
CCS
2010
ACM
13 years 5 months ago
The limits of automatic OS fingerprint generation
Remote operating system fingerprinting relies on implementation differences between OSs to identify the specific variant executing on a remote host. Because these differences can ...
David W. Richardson, Steven D. Gribble, Tadayoshi ...
JMLR
2010
140views more  JMLR 2010»
13 years 2 months ago
Learning Non-Stationary Dynamic Bayesian Networks
Learning dynamic Bayesian network structures provides a principled mechanism for identifying conditional dependencies in time-series data. An important assumption of traditional D...
Joshua W. Robinson, Alexander J. Hartemink
ICCV
2003
IEEE
14 years 9 months ago
A Multi-scale Generative Model for Animate Shapes and Parts
This paper presents a multi-scale generative model for representing animate shapes and extracting meaningful parts of objects. The model assumes that animate shapes (2D simple clo...
Aleksandr Dubinskiy, Song Chun Zhu
ITCC
2005
IEEE
14 years 1 months ago
A Scalable Generative Topographic Mapping for Sparse Data Sequences
We propose a novel, computationally efficient generative topographic model for inferring low dimensional representations of high dimensional data sets, designed to exploit data s...
Ata Kabán