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CVPR
2008
IEEE
16 years 3 months ago
Unsupervised learning of probabilistic object models (POMs) for object classification, segmentation and recognition
We present a new unsupervised method to learn unified probabilistic object models (POMs) which can be applied to classification, segmentation, and recognition. We formulate this a...
Yuanhao Chen, Long Zhu, Alan L. Yuille, HongJiang ...
ACL
2006
15 years 3 months ago
Minimum Risk Annealing for Training Log-Linear Models
When training the parameters for a natural language system, one would prefer to minimize 1-best loss (error) on an evaluation set. Since the error surface for many natural languag...
David A. Smith, Jason Eisner
BMCBI
2010
145views more  BMCBI 2010»
15 years 1 months ago
Clustering metagenomic sequences with interpolated Markov models
Background: Sequencing of environmental DNA (often called metagenomics) has shown tremendous potential to uncover the vast number of unknown microbes that cannot be cultured and s...
David R. Kelley, Steven L. Salzberg
SDM
2009
SIAM
144views Data Mining» more  SDM 2009»
15 years 11 months ago
On Segment-Based Stream Modeling and Its Applications.
The primary constraint in the effective mining of data streams is the large volume of data which must be processed in real time. In many cases, it is desirable to store a summary...
Charu C. Aggarwal
WWW
2002
ACM
16 years 2 months ago
Accelerated focused crawling through online relevance feedback
The organization of HTML into a tag tree structure, which is rendered by browsers as roughly rectangular regions with embedded text and HREF links, greatly helps surfers locate an...
Soumen Chakrabarti, Kunal Punera, Mallela Subraman...