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ICMLA
2008
15 years 3 months ago
Image Segmentation as Learning on Hypergraphs
In this paper, we propose to use hypergraphs as the model for images and pose image segmentation as a machine learning problem in which some pixels (called seeds) are labeled as t...
Lei Ding, Alper Yilmaz
ECML
2007
Springer
15 years 8 months ago
Weighted Kernel Regression for Predicting Changing Dependencies
Abstract. Consider the online regression problem where the dependence of the outcome yt on the signal xt changes with time. Standard regression techniques, like Ridge Regression, d...
Steven Busuttil, Yuri Kalnishkan
ICML
2006
IEEE
16 years 2 months ago
Kernel Predictive Linear Gaussian models for nonlinear stochastic dynamical systems
The recent Predictive Linear Gaussian model (or PLG) improves upon traditional linear dynamical system models by using a predictive representation of state, which makes consistent...
David Wingate, Satinder P. Singh
AAAI
2008
15 years 4 months ago
Active Learning for Pipeline Models
For many machine learning solutions to complex applications, there are significant performance advantages to decomposing the overall task into several simpler sequential stages, c...
Dan Roth, Kevin Small
ICML
2007
IEEE
16 years 2 months ago
Simple, robust, scalable semi-supervised learning via expectation regularization
Although semi-supervised learning has been an active area of research, its use in deployed applications is still relatively rare because the methods are often difficult to impleme...
Gideon S. Mann, Andrew McCallum