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Supervised Locally Linear Embedding

• Dick de Ridder, Olga Kouropteva, Oleg Okun, Matti Pietikäinen, Robert P. W. Duin
• ICANN
• 2003

Locally linear embedding (LLE) is a recently proposed method for unsupervised nonlinear dimensionality reduction. It has a number of attractive features: it does not require an iterative algorithm,… (More)

Selection of the Optimal Parameter value for the Locally Linear Embedding Algorithm

• Olga Kouropteva, Oleg Okun, Matti Pietikäinen
• FSKD
• 2002

The locally linear embedding (LLE) algorithm has recently emerged as a promising technique for nonlinear dimensionality reduction of high-dimensional data. One of its advantages over many similar… (More)

Incremental locally linear embedding

• Olga Kouropteva, Oleg Okun, Matti Pietikäinen
• Pattern Recognition
• 2005

The locally linear embedding (LLE) algorithm belongs to a group of manifold learning methods that not only merely reduce data dimensionality, but also attempt to discover a true low dimensional… (More)

Protein Fold Recognition with K-Local Hyperplane Distance Nearest Neighbor Algorithm

• Oleg Okun
• 2004

This paper deals with protein structure analysis, which is useful for understanding function of proteins and therefore evolutionary relationships, since for proteins, function follows from form… (More)

Page Segmentation and Zone Classification: The State of the Art

• Oleg Okun, David S. Doermann, Matti Pietikäinen
• 1999

K-Local hyperplane distance nearest neighbor algorithm and protein fold recognition

• Oleg Okun
• Pattern Recognition and Image Analysis
• 2007

This paper deals with protein structure analysis, which is useful for understanding the function of proteins and therefore evolutionary relationships, since for proteins, function follows from form… (More)

Feature Selection and Ensemble Methods for Bioinformatics: Algorithmic Classification and Implementations

• Oleg Okun
• 2011

Oleg Okun got an MSc degree in radiophysics and electronics in 1990 from Belarusian State University and a PhD degree in computer science in 1996 from the United Institute of Informatics Problems… (More)

Document skew estimation without angle range restriction

• Oleg Okun, Matti Pietikäinen, Jaakko J. Sauvola
• International Journal on Document Analysis and…
• 1999

The existing skew estimation techniques usually assume that the input image is of high resolution and that the detectable angle range is limited. We present a more generic solution for this task that… (More)

Classification of handwritten digits using supervised locally linear embedding algorithm and support vector machine

• Olga Kouropteva, Oleg Okun, Matti Pietikäinen
• ESANN
• 2003

The locally linear embedding (LLE) algorithm is an unsupervised technique recently proposed for nonlinear dimensionality reduction. In this paper, we describe its supervised variant (SLLE). This is a… (More)

Random Forest for Gene Expression Based Cancer Classification: Overlooked Issues

• Oleg Okun, Helen Priisalu
• IbPRIA
• 2007

Random forest is a collection (ensemble) of decision trees. It is a popular ensemble technique in pattern recognition. In this article, we apply random forest for cancer classification based on gene… (More)

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