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CVPR
2007
IEEE
14 years 3 months ago
Learning Generative Models via Discriminative Approaches
Generative model learning is one of the key problems in machine learning and computer vision. Currently the use of generative models is limited due to the difficulty in effective...
Zhuowen Tu
ICALP
2011
Springer
13 years 3 days ago
New Algorithms for Learning in Presence of Errors
We give new algorithms for a variety of randomly-generated instances of computational problems using a linearization technique that reduces to solving a system of linear equations...
Sanjeev Arora, Rong Ge
AMFG
2005
IEEE
203views Biometrics» more  AMFG 2005»
14 years 2 months ago
Facial Expression Analysis Using Nonlinear Decomposable Generative Models
We present a new framework to represent and analyze dynamic facial motions using a decomposable generative model. In this paper, we consider facial expressions which lie on a one d...
Chan-Su Lee, Ahmed M. Elgammal
TOG
2002
133views more  TOG 2002»
13 years 8 months ago
Interactive motion generation from examples
There are many applications that demand large quantities of natural looking motion. It is difficult to synthesize motion that looks natural, particularly when it is people who mus...
Okan Arikan, David A. Forsyth
ICDM
2003
IEEE
112views Data Mining» more  ICDM 2003»
14 years 1 months ago
Privacy-preserving Distributed Clustering using Generative Models
We present a framework for clustering distributed data in unsupervised and semi-supervised scenarios, taking into account privacy requirements and communication costs. Rather than...
Srujana Merugu, Joydeep Ghosh