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» Learning Generative Models via Discriminative Approaches
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106
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ICML
2007
IEEE
16 years 1 months ago
Dynamic hierarchical Markov random fields and their application to web data extraction
Hierarchical models have been extensively studied in various domains. However, existing models assume fixed model structures or incorporate structural uncertainty generatively. In...
Jun Zhu, Zaiqing Nie, Bo Zhang, Ji-Rong Wen
NIPS
2008
15 years 2 months ago
Supervised Exponential Family Principal Component Analysis via Convex Optimization
Recently, supervised dimensionality reduction has been gaining attention, owing to the realization that data labels are often available and indicate important underlying structure...
Yuhong Guo
122
Voted
BMCBI
2007
145views more  BMCBI 2007»
15 years 18 days ago
Improved benchmarks for computational motif discovery
Background: An important step in annotation of sequenced genomes is the identification of transcription factor binding sites. More than a hundred different computational methods h...
Geir Kjetil Sandve, Osman Abul, Vegard Walseng, Fi...
111
Voted
ICCV
2009
IEEE
16 years 5 months ago
Dimensionality Reduction and Principal Surfaces via Kernel Map Manifolds
We present a manifold learning approach to dimensionality reduction that explicitly models the manifold as a mapping from low to high dimensional space. The manifold is represen...
Samuel Gerber, Tolga Tasdizen, Ross Whitaker
106
Voted
IROS
2009
IEEE
187views Robotics» more  IROS 2009»
15 years 7 months ago
Three-dimensional Limit Cycle Walking with joint actuation
— This paper describes 3D biped walking generation and control based on Limit Cycle Walking. In our study, we use the simplest possible 3D biped model with three DOFs, incorporat...
Kentaro Miyahara, Yuzuru Harada, Dragomir N. Nench...