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» On Bayesian model and variable selection using MCMC
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77
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CVPR
2010
IEEE
15 years 3 months ago
Latent Hierarchical Structural Learning for Object Detection
We present a latent hierarchical structural learning method for object detection. An object is represented by a mixture of hierarchical tree models where the nodes represent objec...
Leo Zhu, Yuanhao Chen, Antonio Torralba, Alan Yuil...
ICML
2008
IEEE
15 years 10 months ago
On the quantitative analysis of deep belief networks
Deep Belief Networks (DBN's) are generative models that contain many layers of hidden variables. Efficient greedy algorithms for learning and approximate inference have allow...
Ruslan Salakhutdinov, Iain Murray
76
Voted
CORR
2007
Springer
164views Education» more  CORR 2007»
14 years 9 months ago
Consistency of the group Lasso and multiple kernel learning
We consider the least-square regression problem with regularization by a block 1-norm, that is, a sum of Euclidean norms over spaces of dimensions larger than one. This problem, r...
Francis Bach
ICRA
2005
IEEE
173views Robotics» more  ICRA 2005»
15 years 3 months ago
Decision Networks for Repair Strategies in Speech-Based Interaction with Mobile Tour-Guide Robots
– The main task of a voice-enabled tour-guide robot in mass exhibition setting is to engage visitors in dialogue and provide as much exhibit information as possible in a limited ...
Plamen J. Prodanov, Andrzej Drygajlo
NIPS
2008
14 years 11 months ago
Clusters and Coarse Partitions in LP Relaxations
We propose a new class of consistency constraints for Linear Programming (LP) relaxations for finding the most probable (MAP) configuration in graphical models. Usual cluster-base...
David Sontag, Amir Globerson, Tommi Jaakkola