- Copyright 2009 IEEE. Published in the IEEE 2009 Inter-national Conference on Acoustics, Speech, and Signal Pro-
- Probabilistic Proactive Timeline Browser Antti Ajanki1
- TKK Dissertations in Information and Computer Science Espoo 2010 TKK-ICS-D17
- Principle of Learning Metrics for Exploratory Data Analysis
- This is a pre-print of a paper accepted for publication in Virtual Reality. The final publication is available at www.springerlink.com. (DOI: 10.1007/s10055-010-0183-5)
- BAYESIAN BICLUSTERING WITH THE PLAID MODEL Jose Caldas, Samuel Kaski
- Multi-Way, Multi-View Learning Ilkka Huopaniemi and Tommi Suvitaival
- # Elsevier Ltd Jaakko Peltonen, Arto Klami, and Samuel Kaski. Improved Learning of Rie
- Learning More Accurate Metrics for SelfOrganizing Maps
- Proc. ICANN'01, in press Clustering Gene Expression Data by Mutual
- Associative Clustering by Maximizing a Bayes Factor
- TKK Dissertations in Information and Computer Science Espoo 2010 TKK-ICS-D19
- Infinite mixtures for multi-relational categorical data Janne Sinkkonen janne.sinkkonen@tkk.fi
- Discriminative Clustering of Yeast Stress Samuel Kaski1,2
- REGULARIZED DISCRIMINATIVE Samuel Kaski, Janne Sinkkonen, and Arto Klami
- Technical Report A62, Helsinki University of Technology, Publications in Computer and Information Science, Espoo, Finland, November 2000. Convergence of a stochastic semisupervised
- Informative Discriminant Analysis Samuel Kaski samuel.kaski@hut.fi
- Expectation Maximization Algorithms for Conditional Likelihoods Jarkko Salojarvi jarkko.salojarvi@hut.fi
- Technical Report A60, Helsinki University of Technology, Laboratory of Computer and Information Science, Espoo, Finland, August 2000.
- Finite Sequential Information Bottleneck (fsIB) Jaakko Peltonen, Janne Sinkkonen, and Samuel Kaski
- TO APPEAR IN IEEE/ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS 1 Probabilistic analysis of probe reliability in
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- Proc. IDEAL 2000, in press Clustering by Similarity in an Auxiliary Space
- Learning from Relevant Tasks Only Samuel Kaski and Jaakko Peltonen
- Comparison of visualization methods for an atlas of gene expression data sets
- Learning when only some of the training data are from the same distribution as test data Jaakko Peltonen1,2
- CONTEXTUAL INFORMATION ACCESS WITH AUGMENTED REALITY , M. Billinghurst2
- Leo Lahti, Samuel Myllykangas, Sakari Knuutila, and Samuel Kaski: De-pendency detection with similarity constraints. Proceedigns of the
- Visualizations for Assessing Convergence and Mixing of MCMC
- Learning to Learn Implicit Queries from Gaze Patterns Kai Puolamaki kai.puolamaki@tkk.fi
- In 'Advances in SelfOrganizing Maps', pp. 224229, Springer, 2001 A Topography-Preserving Latent Variable
- Automatic Choice of Control Measurements Gayle Leen1
- Journal of Machine Learning Research VV (YYYY) PP-PP Submitted 4/09; Revised 12/09; Published MM/YY Information Retrieval Perspective to Nonlinear Dimensionality
- REGULARIZED DISCRIMINATIVE Samuel Kaski, Janne Sinkkonen, and Arto Klami
- Preprint for Lahti et al., MLSP'09 DEPENDENCY DETECTION WITH SIMILARITY CONSTRAINTS
- Learning shared and separate features of two related data sets using GPLVMs
- JMLR: Workshop and Conference Proceedings vol (2010) 17 Workshop on Applications of Pattern Analysis Pinview: Implicit Feedback in Content-Based Image
- To appear in Neural Computation Clustering based on conditional distributions in an
- Discriminative Clustering: Optimal Contingency Tables by Learning Metrics
- IJCNN 2000, To appear. Metrics that learn relevance
- IEEE TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS, VOL. X, NO. Y, MONTH 2005 0 #2005 IEEE. Personal use of this material is permitted. However, permission to reprint/republish
- Learning Metrics for Information Visualization Jaakko Peltonen, Arto Klami and Samuel Kaski
- Visualizing highdimensional posterior distributions in Bayesian modeling
- Can Relevance of Images Be Inferred from Eye Department of Information and Computer
- Inferring vertex properties from topology in large networks
- Two-Way Latent Grouping Model for User Preference Prediction Eerika Savia and Kai Puolamaki
- ASSOCIATIVE CLUSTERING (AC): TECHNICAL DETAILS 1 Associative Clustering (AC): Technical Details
- Proc. IJCNN'01, International Joint Conference on Neural Networks, in press Learning Metrics for Self-Organizing Maps
- On Discriminative Joint Density Modeling Jarkko Salojarvi1
- Discriminative Clustering Samuel Kaski
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- Nonlinear dimensionality reduction viewed as information retrieval
- Hierarchical Generative Biclustering for MicroRNA Expression Analysis
- DISCRIMINATIVE CLUSTERING OF TEXT DOCUMENTS Jaakko Peltonen, Janne Sinkkonen, and Samuel Kaski
- A NeRV projection [4] of 105 experiments, each shown as a glyph. B The slices of each glyph show the distribution of topics in three example experiments. C Enlarged region from A where
- Nonlinear Dimensionality Reduction as Information Retrieval Jarkko Venna and Samuel Kaski
- Local multidimensional scaling Jarkko Venna and Samuel Kaski
- Cross-Species Translation of Multi-Way Tommi Suvitaival1
- Ubiquitous Contextual Information Access with Proactive Retrieval and Augmentation
- BIOINFORMATICS Vol. 26 ISMB 2010, pages i391i398
- Graphical Multi-Way Models Ilkka Huopaniemi1
- TKK Reports in Information and Computer Science Espoo 2009 TKK-ICS-R27
- A block model suitable for sparse graphs Juuso Parkkinen juuso.parkkinen@tkk.fi
- BIOINFORMATICS Vol. 25 ISMB 2009, pages i145i153
- BMC Bioinformatics Poster presentation
- GaZIR: Gaze-based Zooming Interface for Image Retrieval Lszl Kozma
- Bayesian Solutions to the Label Switching Kai Puolamaki and Samuel Kaski
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- Two-level infinite mixture for multi-domain data Simon Rogers
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- Functional Elements and Networks in fMRI Jarkko Ylipaavalniemi1
- Information Retrieval by Inferring Implicit Queries from Eye Movements
- Nonlinear dimensionality reduction viewed as information retrieval Jarkko Venna and Samuel Kaski
- Fast Discriminative Component Analysis for Comparing Examples
- GENERATIVE MODELS THAT DISCOVER DEPENDENCIES BETWEEN DATA SETS Arto Klami, Samuel Kaski
- Visualizing Gene Interaction Graphs with Local Multidimensional Scaling
- Local multidimensional scaling with controlled tradeoff between trustworthiness and continuity
- ASSOCIATIVE CLUSTERING (AC): TECHNICAL DETAILS 1 Associative Clustering (AC): Technical Details
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- Discriminative Clustering Samuel Kaski , Janne Sinkkonen, Arto Klami
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- c 2010 Oxford University Press. This is a preprint version of 'Global mod-eling of transcriptional responses in interaction networks' by Lahti et al.,
- VISUALIZED ATLAS OF A GENE EXPRESSION DATABANK Jarkko Venna1
- Relevant subtask learning by constrained mixture models
- Can relevance be inferred from eye movements in information retrieval?
- Copyright ACM, (2010). This is the author's version of the work. It is posted here by permission of ACM for your
- The self-organizing map as a visual neighbor retrieval method Kristian Nybo1
- Discriminative clustering in Fisher metrics Jarkko Salojarvi, Samuel Kaski and Janne Sinkkonen
- From learning metrics towards dependency exploration Samuel Kaski
- Local Dependent Components Arto Klami arto.klami@tkk.fi
- Two-Way Grouping by One-Way Topic Models Eerika Savia, Kai Puolamaki, and Samuel Kaski
- Combining Eye Movements and Collaborative Filtering for Proactive Information Retrieval
- Neural Networks for Signal Processing XI Proceedings of the 2001 IEEE Workshop, in press LEARNING METRICS FOR EXPLORATORY
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- Generative Modeling for Maximizing Precision and Recall in Information Visualization
- TKK Reports in Information and Computer Science Espoo 2010 TKK-ICS-R38
- Focused Multi-task Learning Using Gaussian Gayle Leen1,2
- Detecting similar high-dimensional responses to experimental factors from human and model
- Data-Driven Information Retrieval in Heterogeneous Collections of Transcriptomics Data Links SIM2s to
- Systematic Use of Computational Methods Allows Stratifying Treatment Responders in Glioblastoma Multiforme
- Biomarker discovery via dependency analysis of multi-view functional genomics data
- International Scholarly Research Network ISRN Oncology
- Bayesian CCA via Group Sparsity Seppo Virtanen1
- Bayesian exponential family projections for coupled data sources Arto Klami, Seppo Virtanen, Samuel Kaski
- Combining Data Sources Nonlinearly for Cell Nucleus Classification of Renal Cell Carcinoma
- Multitask Learning Using Regularized Multiple Kernel Learning
- Metabolic Regulation in Progression to Autoimmune Marko Sysi-Aho1
- High Density Lipoprotein Structural Changes and Drug Response in Lipidomic Profiles following the Long-Term
- Sparse Nonparametric Topic Model for Transfer Ali Faisal1
