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JMLR
2010
141views more  JMLR 2010»
14 years 4 months ago
FastInf: An Efficient Approximate Inference Library
The FastInf C++ library is designed to perform memory and time efficient approximate inference in large-scale discrete undirected graphical models. The focus of the library is pro...
Ariel Jaimovich, Ofer Meshi, Ian McGraw, Gal Elida...
CVPR
2007
IEEE
15 years 11 months ago
Tracking as Repeated Figure/Ground Segmentation
Tracking over a long period of time is challenging as the appearance, shape and scale of the object in question may vary. We propose a paradigm of tracking by repeatedly segmentin...
Xiaofeng Ren, Jitendra Malik
AAAI
2011
13 years 9 months ago
Coarse-to-Fine Inference and Learning for First-Order Probabilistic Models
Coarse-to-fine approaches use sequences of increasingly fine approximations to control the complexity of inference and learning. These techniques are often used in NLP and visio...
Chloe Kiddon, Pedro Domingos
ICML
2009
IEEE
15 years 10 months ago
Hilbert space embeddings of conditional distributions with applications to dynamical systems
In this paper, we extend the Hilbert space embedding approach to handle conditional distributions. We derive a kernel estimate for the conditional embedding, and show its connecti...
Le Song, Jonathan Huang, Alexander J. Smola, Kenji...
JMLR
2011
167views more  JMLR 2011»
14 years 4 months ago
Logistic Stick-Breaking Process
A logistic stick-breaking process (LSBP) is proposed for non-parametric clustering of general spatially- or temporally-dependent data, imposing the belief that proximate data are ...
Lu Ren, Lan Du, Lawrence Carin, David B. Dunson