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» Unsupervised Learning Using MML
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165
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CSDA
2007
169views more  CSDA 2007»
15 years 3 months ago
A null space method for over-complete blind source separation
In blind source separation, there are M sources that produce sounds independently and continuously over time. These sounds are then recorded by m receivers. The sound recorded by ...
Ray-Bing Chen, Ying Nian Wu
WCRE
2010
IEEE
15 years 2 months ago
Software Process Recovery: Recovering Process from Artifacts
—Often stakeholders, such as developers, managers, or buyers, want to find out what software development processes are being followed within a software project. Their reasons in...
Abram Hindle
182
Voted
JMLR
2010
179views more  JMLR 2010»
14 years 10 months ago
PAC-Bayesian Analysis of Co-clustering and Beyond
We derive PAC-Bayesian generalization bounds for supervised and unsupervised learning models based on clustering, such as co-clustering, matrix tri-factorization, graphical models...
Yevgeny Seldin, Naftali Tishby
176
Voted
CVPR
2009
IEEE
16 years 10 months ago
Vocabulary Hierarchy Optimization for Effective and Transferable Retrieval
Scalable image retrieval systems usually involve hierarchical quantization of local image descriptors, which produces a visual vocabulary for inverted indexing of images. Although ...
Rongrong Ji (Harbin Institute of Technology), Xing...
139
Voted
JCDL
2009
ACM
139views Education» more  JCDL 2009»
15 years 10 months ago
Topic model methods for automatically identifying out-of-scope resources
Recent years have seen the rise of subject-themed digital libraries, such as the NSDL pathways and the Digital Library for Earth System Education (DLESE). These libraries often ne...
Steven Bethard, Soumya Ghosh, James H. Martin, Tam...