to appear |
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9 | Mikael Kuusela, Tommi Vatanen, Eric Malmi, Tapani Raiko, Timo Aaltonen, and Yoshikazu Nagai. Semi-supervised anomaly detection - towards model-independent searches of new physics. Journal of Physics: Conference Series, to appear. |
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2011 |
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8 | Tommi Vatanen, Mikael Kuusela, Eric Malmi, Tapani Raiko, Timo Aaltonen, and Yoshikazu Nagai. Fixed-background EM algorithm for semi-supervised anomaly detection. Technical report, Aalto University School of Science, 2011. |
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7 | Mikael Kuusela, Eric Malmi, Risto Orava, and Tommi Vatanen. Soft classification of diffractive interactions at the LHC. AIP Conference Proceedings, 1350(1):111–114, 2011. |
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2010 |
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6 | Tommi Vatanen, Mikael Kuusela, Eric Malmi, and Risto Orava. Anomaly search with density estimation and EM algorithm. 6th International Summer School on Pattern Recognition, ISSPR 2010, September 2010. Poster. |
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5 | Mikael Kuusela, Eric Malmi, Tommi Vatanen, Risto Orava, Timo Aaltonen, and Yoshikazu Nagai. Detection of new physics using density estimation based anomaly search. CDF/DOC/EXOTIC/CDFR/10227 (Internal note), 2010. |
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4 | Antti Honkela, Tapani Raiko, Mikael Kuusela, Matti Tornio, and Juha Karhunen. Approximate Riemannian conjugate gradient learning for fixed-form variational Bayes. Journal of Machine Learning Research, 11(Nov):3235–3268, 2010. |
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3 | Mikael Kuusela, Jerry W. Lämsä, Eric Malmi, Petteri Mehtälä, and Risto Orava. Multivariate techniques for identifying diffractive interactions at the LHC. International Journal of Modern Physics A, 25(8):1615–1647, 2010. |
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2009 |
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2 | Mikael Kuusela, Tapani Raiko, Antti Honkela, and Juha Karhunen. A gradient-based algorithm competitive with variational Bayesian EM for mixture of Gaussians. In Proceedings of the International Joint Conference on Neural Networks, IJCNN 2009, pages 1688–1695, Atlanta, Georgia, June 2009. |
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1 | Mikael Kuusela. Algorithms for variational learning of mixture of Gaussians, 2009. Bachelor's thesis. |
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