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» A Framework for Multiple-Instance Learning
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CCIA
2009
Springer
15 years 7 months ago
Measuring Interest of Human Dyadic Interactions
In this paper, we argue that only using behavioural motion information, we are able to predict the interest of observers when looking at face-to-face interactions. We propose a set...
Sergio Escalera, Oriol Pujol, Petia Radeva, Jordi ...
ICML
2010
IEEE
15 years 7 months ago
Mixed Membership Matrix Factorization
Discrete mixed membership modeling and continuous latent factor modeling (also known as matrix factorization) are two popular, complementary approaches to dyadic data analysis. In...
Lester W. Mackey, David Weiss, Michael I. Jordan
ICML
2010
IEEE
15 years 7 months ago
Modeling Interaction via the Principle of Maximum Causal Entropy
The principle of maximum entropy provides a powerful framework for statistical models of joint, conditional, and marginal distributions. However, there are many important distribu...
Brian Ziebart, J. Andrew Bagnell, Anind K. Dey
ICML
2010
IEEE
15 years 7 months ago
An Analysis of the Convergence of Graph Laplacians
Existing approaches to analyzing the asymptotics of graph Laplacians typically assume a well-behaved kernel function with smoothness assumptions. We remove the smoothness assumpti...
Daniel Ting, Ling Huang, Michael I. Jordan
CVPR
2010
IEEE
15 years 6 months ago
Deconvolutional networks
Building robust low and mid-level image representations, beyond edge primitives, is a long-standing goal in vision. Many existing feature detectors spatially pool edge information...
Matthew D. Zeiler, Dilip Krishnan, Graham W. Taylo...