Lasse Holmström - researchr alias

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Viewing Publication 1 - 20 from 20

2018

A scale space approach for exploring structure in spherical dataVille Vuollo, Lasse Holmström. csda, 125:57-69, 2018. [doi]

2017

Estimation of level set trees using adaptive partitionsLasse Holmström, Kyösti Karttunen, Jussi Klemelä. cstat, 32(3):1139-1163, 2017. [doi]

Multivariate posterior singular spectrum analysisIlkka Launonen, Lasse Holmström. sma, 26(3):361-382, 2017. [doi]

Modeling probability density through ultraspherical polynomial transformationsTerhi Mäkinen, Lasse Holmström. cssc, 46(8):5879-5900, 2017. [doi]

Scale space multiresolution correlation analysis for time series dataLeena Pasanen, Lasse Holmström. cstat, 32(1):197-218, 2017. [doi]

2014

Level Set Trees with Enhanced Marginal Density VisualizationKyösti Karttunen, Lasse Holmström, Jussi Klemelä. grapp 2014: 210-217 [doi]

2013

Posterior singular spectrum analysisLasse Holmström, Ilkka Launonen. sadm, 6(5):387-402, 2013. [doi]

Bayesian scale space analysis of imagesLeena Pasanen, Lasse Holmström. imspa 2013: 96-100 [doi]

2012

Bayesian Scale Space Analysis of Differences in ImagesLasse Holmström, Leena Pasanen. technometrics, 54(1):16-29, 2012. [doi]

2011

Scale space multiresolution analysis of random signalsLasse Holmström, Leena Pasanen, Reinhard Furrer, Stephan R. Sain. csda, 55(10):2840-2855, 2011. [doi]

2004

Application of Semiparametric Density Estimation to ClassificationLasse Holmström, Fabian Hoti. icpr 2004: 371-374 [doi]

A semiparametric density estimation approach to pattern classificationFabian Hoti, Lasse Holmström. PR, 37(3):409-419, 2004. [doi]

2002

Making inferences about past environmental change using smoothing in multiple time scalesLasse Holmström, Panu Erästö. csda, 41(2):289-309, 2002. [doi]

1997

Neural and statistical classifiers-taxonomy and two case studiesLasse Holmström, Petri Koistinen, Jorma Laaksonen, Erkki Oja. tnn, 8(1):5-17, 1997. [doi]

1996

Neural network and statistical perspectives of classificationLasse Holmström, Petri Koistinen, Jorma Laaksonen, Erkki Oja. icpr 1996: 286-290 [doi]

Complexity Reduction in Probabilistic Neural NetworksAri Hämäläinen, Lasse Holmström. icann 1996: 65-70

1993

The self-organizing reduced kernel density estimatorLasse Holmström, Ari Hämäläinen. icnn 1993: 417-421 [doi]

1992

Using additive noise in back-propagation trainingLasse Holmström, Petri Koistinen. tnn, 3(1):24-38, 1992. [doi]

1991

Kernel Regression and Backpropagation Training With NoisePetri Koistinen, Lasse Holmström. nips 1992: 1033-1039 [doi]

1987

Piecewise quadric blending of implicitly defined surfacesLasse Holmström. cagd, 4(3):171-189, 1987. [doi]

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