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.

  • 09.06.2014 13:15–14:00
    HIIT seminar
    Aalto University, Computer Science Building, lecture hall T2

    Abstract:
    Self-assembly is a process through which disorganized, relatively simple components autonomously coalesce according to local rules to form more complex target structures, in the absence of orders from an external global conductor. DNA self-assembly can produce various nanoscale structures experimentally, including regular arrays, fractal structures, simley faces...

  • 06.06.2014 10:15–11:15
    HIIT seminar
    Kumpula, Exactum B119
    Title: High-Dimensional Incremental Divisive Clustering under Population Drift
     
    Abstract: Clustering is a central problem in data mining and statistical pattern recognition with a long and rich history. The advent of Big Data has introduced important challenges to existing clustering methods in the form of high-dimensional, high-frequency, time-varying streams of data. Up-to-date...
  • Big Data or Right Data?

    Dr. Ricardo Baeza-Yates, Yahoo! Labs, Barcelona

    Abstract:

    Big data nowadays is a fashionable topic, independently of what people mean when they use this term. But being big is just a matter of volume, although there is no clear agreement in the size threshold. On the other hand, it is easy to capture large amounts of data using a brute force approach. So the real goal should not be big data but to ask ourselves, for a given problem, what is the right data and...

  • 02.06.2014 13:15–14:00
    HIIT seminar
    Aalto University, Computer Science Building, lecture hall T2

    Abstract:
    Sequences of events are an ubiquitous form of data. In this paper, we show that it is feasible to present an event sequence as an interval sequence. We show how sequences can be efficiently randomized, how to choose a correct null model and how to use randomizations to derive confidence intervals. Using these techniques, we gain knowledge of the temporal...

  • 30.05.2014 10:15–11:15
    HIIT seminar
    Kumpula, Exactum B119
     
    Title: High-Dimensional Incremental Divisive Clustering under Population Drift
     
    Abstract: Clustering is a central problem in data mining and statistical pattern recognition with a long and rich history. The advent of Big Data has introduced important challenges to existing clustering methods in the form of high-dimensional, high-frequency, time-varying streams...
  • The Public Sector Information Exchange (PSIE)

    Prof. Alon Peled, The Hebrew University of Jerusalem, Israel

    Abstract:

    We are creating a Public Sector Information Exchange (PSIE) software platform to help agencies[1] discover and exchange governmental information assets. Our platform first helps agencies automatically discover, catalogue, analyze, and expand metadata[2] information about the information assets that already exist on these agencies' servers.[3] Next, the software...

  • Current Topics in Image Synthesis

    Prof. Jaakko Lehtinen, Department of Media, Aalto

    Abstract:

    In this this talk, I will provide an overview of modern computer graphics. In particular, I will outline important open problems in realistic (physically-based) image synthesis, and describe the research we perform in my new group in order to address these challenges.

    About the speaker:

    https://mediatech.aalto.fi/~jaakko/

    Host: Antti Ukkonen

  • 19.05.2014 13:15–14:00
    HIIT seminar
    Aalto University, Computer Science Building, lecture hall T2

    Abstract:  In this this talk, I will provide an overview of modern computer graphics. In particular, I will outline important open problems in realistic (physically-based) image synthesis, and describe the research we perform in my new group in order to address these challenges.

    About the speaker:
    https://mediatech.aalto.fi/~jaakko/
     

  • Innovation, Preferential Growth and Memory in Chess Playing Behavior

    Dr. Juan Ignacio Perotti, BECS, Aalto University

    Abstract:

    Complexity develops via the incorporation of innovative properties. Chess is one of the most complex strategy games where expert contenders exercise decision making by imitating old games or introducing innovative moves. We found that chess players tend to innovate with a probability decaying as a power law of the popularity of the last played move. By...

  • 12.05.2014 13:15–14:00
    HIIT seminar
    Aalto University, Computer Science Building, lecture hall T2

    Complexity develops via the incorporation of innovative properties.
    Chess is one of the most complex strategy games where expert
    contenders exercise decision making by imitating old games or
    introducing innovative moves. We found that chess players tend to
    innovate with a probability decaying as a power law of the popularity
    of the last played...

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