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» Unifying generative and discriminative learning principles
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C5
2004
IEEE
9 years 2 months ago
Enabling Social Dimensions of Learning through a Persistent, Unified, Massively Multi-User, and Self-Organizing Virtual Environm
Existing online learning experiences lack the social dimension that characterizes learning in the real world. This social dimension extends beyond the traditional classroom into t...
Julian Lombardi, Mark P. McCahill
ICCV
2005
IEEE
10 years 9 days ago
Combining Generative Models and Fisher Kernels for Object Recognition
Learning models for detecting and classifying object categories is a challenging problem in machine vision. While discriminative approaches to learning and classification have, in...
Alex Holub, Max Welling, Pietro Perona
JMLR
2010
191views more  JMLR 2010»
8 years 5 months ago
Noise-contrastive estimation: A new estimation principle for unnormalized statistical models
We present a new estimation principle for parameterized statistical models. The idea is to perform nonlinear logistic regression to discriminate between the observed data and some...
Michael Gutmann, Aapo Hyvärinen
SIGIR
2010
ACM
9 years 2 months ago
Discriminative models of integrating document evidence and document-candidate associations for expert search
Generative models such as statistical language modeling have been widely studied in the task of expert search to model the relationship between experts and their expertise indicat...
Yi Fang, Luo Si, Aditya P. Mathur
ICML
2008
IEEE
9 years 11 months ago
Extracting and composing robust features with denoising autoencoders
Previous work has shown that the difficulties in learning deep generative or discriminative models can be overcome by an initial unsupervised learning step that maps inputs to use...
Pascal Vincent, Hugo Larochelle, Yoshua Bengio, Pi...
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