Helsinki ICT Research Events

This event feed aggregates content from the Research Events feeds from the Helsinki Institute for Information Technology HIIT, Aalto University Department of Computer Science, and the University of Helsinki Department of Computer Science.

  • 30.09.2013 13:15–14:00
    HIIT seminar
    Aalto University, Computer Science Building, lecture hall T2

    Abstract:
    The presentation takes a look at Rovio’s cloud based analytics
    solution (Stats), and covers some challenges and victories that the
    development team has experienced from both the past and the present.

    Bio:
    Hannes Heikinheimo is development lead on Rovio's big data and
    analytics pipeline. He is a data scientist...

  • M.Sc. Antti Ajanki will defend his doctoral dissertation Inference of relevance for proactive information retrieval on 27 September 2013 in lecture hall T2 (Computer Science building). The opponent is Prof. Kari-Jouko Räihä, Tampereen yliopisto. The custodian is Prof. Samuel Kaski.

    Announcement (fi, pdf)

  • 27.09.2013 12:15–14:00
    Guest lecture
    CK112

    Facebook Engineering Tech Talk for students and faculty members:
    Graph Search & Cryptography

    Please note that this guest lecture is different from the student event on Thursday, September 26th (at www.facebook.com/UniversityofHelsinki )

    All students and faculty welcome! 

  • 27.09.2013 12:00–16:00
    Doctoral dissertation
    lecture hall T2 of the Computer Science building of Aalto University, Konemiehentie 2, Espoo

    Search engines have become very important as the amount of digital
    data has grown dramatically. The most common search interfaces require
    one to describe an information need using a small number of search
    terms, but that is not feasible in all situations. Expressing a
    complex query as precise search terms is...

  • 27.09.2013 10:15–11:00
    HIIT seminar
    Exactum, B119
    Title
    Distributed algorithms and computational algorithm design
     
    Abstract
    We discuss how to use computational techniques to develop novel distributed algorithms. That is, how to use computers to find (a) provably correct algorithms or (b) a proof non-existence for certain types of algorithms. This work showcases the use of modern-day SAT solvers which can solve...
  • 27.09.2013 10:15–11:00
    HIIT seminar
    Exactum, B119
    Title
    Distributed algorithms and computational algorithm design
     
    Abstract
    We discuss how to use computational techniques to develop novel distributed algorithms. That is, how to use computers to find (a) provably correct algorithms or (b) a proof non-existence for certain types of algorithms. This work showcases the use of modern-day SAT solvers which can solve...
  • 20.09.2013 12:00–16:00
    Defence of thesis
    University of Helsinki Main Building, Auditorium XII, Unioninkatu 34
  • 20.09.2013 12:00–16:00
    Doctoral dissertation
    University of Helsinki Main Building, Auditorium XII, Unioninkatu 34

    The context and motivation for this thesis is gene mapping, the discovery of genetic variants that affect susceptibility to disease. The goals of gene mapping research include understanding of disease mechanisms, evaluating individual disease risks and ultimately developing new medicines and treatments.

    Traditional genetic association mapping methods test...

  • 20.09.2013 10:15–11:00
    HIIT seminar
    Exactum, B119
    Title
    Treedy: A Heuristic for Counting and Sampling Subsets
     
    Abstract
    Consider a collection of weighted subsets of a ground set N. Given a query subset Q of N, how fast can one (1) find the weighted sum over all subsets of Q, and (2) sample a subset of Q proportionally to the weights? We present a tree-based greedy heuristic, Treedy, that for a given positive...
  • 20.09.2013 10:15–11:00
    HIIT seminar
    Exactum, B119
    Title
    Treedy: A Heuristic for Counting and Sampling Subsets
     
    Abstract
    Consider a collection of weighted subsets of a ground set N. Given a query subset Q of N, how fast can one (1) find the weighted sum over all subsets of Q, and (2) sample a subset of Q proportionally to the weights? We present a tree-based greedy heuristic, Treedy, that for a given positive...

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