Helsinki University of
Technology
Laboratory of Computer
and Information Science
Neural Networks Research
Centre
From Data To
Knowledge Research Unit (research projects under the
CIS laboratory)
Biennial report 2004-2005
V. Könönen, K. Raivio, R. Vigário,
and L. Koivisto, editors
Otaniemi, April 2006
ISSN 1796-4121 (electronic version)
ISSN 1795-5092 (printed version)
Contents
Full report as a PDF
file
Contents as
a PDF file
- Preface [PDF]
- Personnel [PDF]
- Awards and activities [PDF]
- Courses [PDF]
- Doctoral dissertations [PDF]
- Theses [PDF]
- 1. Introduction PDF
- 2. Independent component analysis and blind source separation PDF
- 2.1 Introduction
- 2.2 Finite sample behaviour of the FastICA algorithm
- 2.3 Nonlinear ICA and BSS
- 2.4 Denoising source separation
- 2.5 Climate data analysis with DSS
- 2.6 ICA and denoising source separation in CDMA communications
- 2.7 ICA for image representations
- 2.8 Analyzing 0-1 data
- 3. Neuroinformatics PDF
- 3.1 Setup of the group
- 3.2 Source localization of low- and high-amplitude alpha activity
- 3.3 DSS extraction of the cardiac subspace in MEG
- 4. Variational Bayesian learning of generative models PDF
- 4.1 Bayesian modeling and variational learning: introduction
- 4.2 Theoretical improvements
- 4.3 Building blocks for variational Bayesian learning
- 4.4 Nonlinear and non-negative blind source separation
- 4.5 Dynamic modelling using nonlinear state-space models
- 4.6 Relational models
- 4.7 Applications to astronomy
- 5. Bioinformatics PDF
- 5.1 Introduction
- 5.2 Yeast systems biology
- 5.3 Comparative functional genomics
- 5.4 Gene expression atlas
- 5.5 Genomics of human endogenous retroviruses
- 6. Dependency exploration and learning metrics PDF
- 6.1 Introduction
- 6.2 Supervised unsupervised learning
- 6.3 Dependency exploration
- 6.4 Discriminative learning
- 6.5 Visualization methods
- 7. Image retrieval and analysis PDF
- 7.1 Content-based image retrieval by self-organizing maps
- 7.2 Content-based retrieval of defect images
- 7.3 Alterable volume flow in the use of input deformations for
a massive Gaussian process smoothing
- 7.4 Stopping criteria for nonlinear diffusion filters
- 8. Adaptive cognitive systems PDF
- 8.1 Introduction
- 8.2 Emergence of cognitive and conceptual representations
- 8.3 Reinforcement learning in multiagent systems
- 9. Speech recognition PDF
- 9.1 The speech recognition tasks and systems
- 9.2 Acoustic modeling
- 9.3 Language modeling
- 9.4 Large vocabulary decoder
- 9.5 Spoken document retrieval
- 10. Natural language processing PDF
- 10.1 Unsupervised segmentation of words into morphs
- 10.2 Word sense disambiguation using document maps
- 10.3 Topically focusing language model
- 10.4 Emergence of linguistic features using
independent component analysis
- 10.5 SOM-based analysis of words and sentences
- 11. Intelligent data engineering PDF
- 11.1 A knowledge-based model for analysis of GSM network
performance
- 11.2 Analysis of mobile radio access network
- 11.3 Using visualization, variable selection and feature extraction to learn from industrial data
- 11.4 SOM in decision support
- 11.5 Interpreting dependencies in data using the Self-Organizing Map
- 11.6 Analysis of forest nutrition data
- 11.7 Parsimonious signal representations in data analysis
- 12. Time series prediction PDF
- 12.1 Introduction
- 12.2 The CATS benchmark
- 12.3 Methodology for long-term prediction of time series
- 12.4 Input selection strategies
- 12.5 Chemometry
- 13. Proactive information retrieval PDF
- 13.1 Introduction
- 13.2 Implicit relevance feedback from eye movements
- 13.3 Collaborative Filtering: Inferring user interests from other available sources
- 13.4 Application: Proactive information retrieval
- 14. Other projects PDF
- 14.1 Adaptive committee techniques
- 14.2 Data analysis using the Evolving Tree
- 14.3 Independent variable group analysis
- 14.4 Worldwide research on and using the Self-Organizing Map
- 14.5 Self-Organizing Neural Projections
- 14.6 Applications of the Self-Organizing Map
- Publications of the Neural Networks Research Centre PDF
- 15. From Data to Knowledge Research Unit PDF
- 15.1 Data mining at the Pattern Discovery group
- 15.2 Discovering orderings
- 15.3 Theoretical aspects of data mining
- 15.4 Extending frequent itemsets: dense itemsets and tiles
- 15.5 Basis segmentation
- 15.6 Data mining in bioinformatics
- Publications of the From Data to Knowledge Research Unit PDF