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ICML
2003
IEEE
14 years 8 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
CORR
2011
Springer
177views Education» more  CORR 2011»
12 years 11 months ago
Gossip PCA
Eigenvectors of data matrices play an important role in many computational problems, ranging from signal processing to machine learning and control. For instance, algorithms that ...
Satish Babu Korada, Andrea Montanari, Sewoong Oh
SDM
2010
SIAM
181views Data Mining» more  SDM 2010»
13 years 5 months ago
Efficient Nonnegative Matrix Factorization with Random Projections
The recent years have witnessed a surge of interests in Nonnegative Matrix Factorization (NMF) in data mining and machine learning fields. Despite its elegant theory and empirical...
Fei Wang, Ping Li
ICMLA
2008
13 years 9 months ago
Comprehensible Models for Predicting Molecular Interaction with Heart-Regulating Genes
When using machine learning for in silico modeling, the goal is normally to obtain highly accurate predictive models. Often, however, models should also bring insights into intere...
Cecilia Sönströd, Ulf Johansson, Ulf Nor...
ACIVS
2006
Springer
13 years 11 months ago
Robust Analysis of Silhouettes by Morphological Size Distributions
We address the topic of real-time analysis and recognition of silhouettes. The method that we propose first produces object features obtained by a new type of morphological operato...
Olivier Barnich, Sébastien Jodogne, Marc Va...