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ICML
2008
IEEE
16 years 7 months ago
Training structural SVMs when exact inference is intractable
While discriminative training (e.g., CRF, structural SVM) holds much promise for machine translation, image segmentation, and clustering, the complex inference these applications ...
Thomas Finley, Thorsten Joachims
ICML
2008
IEEE
16 years 7 months ago
Bayesian probabilistic matrix factorization using Markov chain Monte Carlo
Low-rank matrix approximation methods provide one of the simplest and most effective approaches to collaborative filtering. Such models are usually fitted to data by finding a MAP...
Ruslan Salakhutdinov, Andriy Mnih
ICML
2005
IEEE
16 years 7 months ago
Beyond the point cloud: from transductive to semi-supervised learning
Due to its occurrence in engineering domains and implications for natural learning, the problem of utilizing unlabeled data is attracting increasing attention in machine learning....
Vikas Sindhwani, Partha Niyogi, Mikhail Belkin
ICML
2004
IEEE
16 years 7 months ago
Utile distinction hidden Markov models
This paper addresses the problem of constructing good action selection policies for agents acting in partially observable environments, a class of problems generally known as Part...
Daan Wierstra, Marco Wiering
ICML
2003
IEEE
16 years 7 months ago
Semi-Supervised Learning Using Gaussian Fields and Harmonic Functions
An approach to semi-supervised learning is proposed that is based on a Gaussian random field model. Labeled and unlabeled data are represented as vertices in a weighted graph, wit...
Xiaojin Zhu, Zoubin Ghahramani, John D. Lafferty
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