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ICDM
2008
IEEE
115views Data Mining» more  ICDM 2008»
14 years 4 months ago
Toward Faster Nonnegative Matrix Factorization: A New Algorithm and Comparisons
Nonnegative Matrix Factorization (NMF) is a dimension reduction method that has been widely used for various tasks including text mining, pattern analysis, clustering, and cancer ...
Jingu Kim, Haesun Park
IJCAI
2007
13 years 11 months ago
A Theoretical Framework for Learning Bayesian Networks with Parameter Inequality Constraints
The task of learning models for many real-world problems requires incorporating domain knowledge into learning algorithms, to enable accurate learning from a realistic volume of t...
Radu Stefan Niculescu, Tom M. Mitchell, R. Bharat ...
MM
2010
ACM
137views Multimedia» more  MM 2010»
13 years 10 months ago
Unsupervised summarization of rushes videos
This paper proposes a new framework to formulate the problem of rushes video summarization as an unsupervised learning problem. We pose the problem of video summarization as one o...
Yang Liu, Feng Zhou, Wei Liu, Fernando De la Torre...
CVPR
2009
IEEE
15 years 5 months ago
Optimization of Landmark Selection for Cortical Surface Registration
Manually labeled landmark sets are often required as in- puts for landmark-based image registration. Identifying an optimal subset of landmarks from a training dataset may be us...
Anand A. Joshi, David W. Shattuck, Dimitrios Panta...
ICCD
2007
IEEE
183views Hardware» more  ICCD 2007»
14 years 7 months ago
Constraint satisfaction in incremental placement with application to performance optimization under power constraints
We present new techniques for explicit constraint satisfaction in the incremental placement process. Our algorithm employs a Lagrangian Relaxation (LR) type approach in the analyt...
Huan Ren, Shantanu Dutt