KTH Mathematics  


Timo Koski

  • Papers 2008-- :

    • Corander, J. & Koski, T. & Pavlenko, T & Tillander, A. (2013): Bayesian Block-Diagonal Predictive Classifier for Gaussian Data. Synergies of Soft Computing and Statistics for Intelligent Data Analysis Advances in Intelligent Systems and Computing Volume 190, 2013, pp 543-551 Link

    • Koski, T. & Noble, J (2012): A Review of Bayesian Networks and Structure Learning. Mathematica Applicanda (Matematyka Stosowana) Link

    • Corander, J. and Xiong, J. & Cui, Y. and Koski, T. (2012): Optimal Viterbi Bayesian predictive classification for data from finite alphabets. Journal of Statistical Planning and Inference. Link

    • J. Corander, Y. Cui, & T. Koski (2012): Inductive Inference and Partiton Exchangeability in Classifiction. Ray Solomonoff Conference, Lecture Notes in Computer Science (in press)

    • M. Singull & Koski, T. (2012). On the Distribution of Matrix Quadratic Forms. Communications in Statistics - Theory and Methods (CIS). Link

    • J. Corander, Y. Cui, T. Koski & J. Siren(2011): Have I Seen You Before ? Principles of Bayesian Predictive Classification Revisited. Statistics and Computing Link

    • T. Koski, Timo E. Sandström, & U. Sandström (2011): Estimating Research Productivity from a Zero-Truncated Distribution. PROCEEDINGS OF THE 13TH CONFERENCE OF THE INTERNATIONAL SOCIETY FOR SCIENTOMETRICS AND INFORMETRICS, VOLS 1 AND 2, Pages: 747-755. Link

    • J. Corander, M. Gyllenberg & T.Koski(2011): Learning Genetic Population Structures Using Minimization of Stochastic Complexity. Entropy; Link

    • J. Corander, M.Ekdahl & T.Koski (2009): Bayesian Unsupervised Learning of DNA Regulatory Binding Regions (in Advances in Artificial Intelligence 2009) Link

    • J. Corander, M.Gyllenberg & T.Koski (2009): Bayesian unsupervised classification framework based on stochastic partitions of data and a parallel search strategy (in Advances in Data Analysis and Classification 2009) Link

    • J. Corander, M.Ekdahl & T.Koski (2008): Parallell interacting MCMC for learning of graph topologies (in Data Mining and Knowledge Discovery 2008) Link


  • A preprint on measurement of research productivity (2011):


  • Papers (2003-2007) via LiU Research Database:

    • The complete list (two pages) Link


  • Computer science library:


  • Recent selected papers from LiU Research Database:

    • M.Ekdahl & T.Koski (2007): On Concentration of Discrete Distributions with Applications to Supervised Learning of Classifiers Link

    • J. Corander, M. Gyllenberg, & T.Koski (2007): Random Partition Models and Exchangeability for Bayesian Identification of Population StructureLink

    • M.Ekdahl & T.Koski (2006): Bounds for the Loss in Probability of Correct Classification Under Model Based Approximation Link


  • Preprints/technical reports:

    • Timo Koski and Roland Orre (1998): Statistics of the Information Component in Bayesian Neural Networks. pdf

    • Mats Gyllenberg and Timo Koski (2001): Probabilistic Models for Bacterial Taxonomy Link

    • Mats Gyllenberg, Timo Koski and Tatu Lund (2001): BinClass: A Software Package for Classifying Binary Vectors User's Guide Link

    • Linus Göransson and Timo Koski (2002): Using a Dynamic Bayesian Network to Learn Genetic Interactions. pdf

    • Mats Gyllenberg, Jonas Carlsson and Timo Koski (2002): Bayesian Network Classification of Binarized DNA Fingerprint Patterns. ps

    • Harry Hurd and Timo Koski (2002): The Wold isomorphism for cyclostationary sequences. pdf



  • A news item from 'Microbiology` :



    Senast uppdaterad 2007-11-23.