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.
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17.03.2014 13:15–14:00
HIIT seminar
Aalto University, Computer Science Building, lecture hall T2Abstract:
The power of human computation is founded on the capabilities of
humans to process qualitative information in a manner that is hard to
reproduce with a computer. However, all machine learning algorithms
rely on mathematical operations, such as sums, averages, least squares
etc. that are less suitable for human computation.
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14.03.2014 14:15–16:00
Guest lecture
CK112Finland as best location for Datacenters
On Friday, March 14th at 14:00 (2 p.m.) we'll have a presentation from Yandex' Head of DC Operations, Aleksei Zhumykin in CK112, Exactum building.
This talk is very relevant for everybody interested in large-scale distributed systems and data centers, as Yandex runs Russia's largest search engine.
Yandex has recently...
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13.03.2014 16:00–18:00
Guest lecture
B123 Linus Torvalds AuditoriumOletko koskaan miettinyt, miksi toiset softat menestyvät ja toiset eivät koskaan löydä käyttäjiään?
RAPID -illassa alan KOVAT ammattilaiset kesustelevat näkökulmistaan siitä, mikä on nopean prototyyppailun rooli nykyaikaisessa ohjelmistokehityksessä. Kolme viidestä puhujasta on oman laitoksemme kasvatteja. Myös SINÄ olet...
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25.02.2014 10:15–11:00
Guest lecture
C222
Machine Learning and Automated Programming in a Computational Creativity contextAbstract
Software writing software is a major research direction for researchers in the field of Computational Creativity, where we study how to write systems that can take on some of the creative responsibility in arts and science projects. In the talk, I will motivate some of the many issues in the field, and how automating programming addresses... -
24.02.2014 14:00–16:00
HIIT seminar
Open Innovation House, 2nd floor, sofa corner, Otaniementie 19B, EspooOur monthly INUSE-seminar continues next Monday, 24.2.2014 14-16 in Otaniemi (more info below). The next presentation by Mikael Johnson concerns one of the significant under-researched topics of user involvement and user studies in design today:... -
21.02.2014 10:15–11:15
HIIT seminar
Exactum B119Title:MCMC-driven Adaptive Multiple Importance SamplingAbstract:Monte Carlo (MC) methods are widely used for statistical inference and stochastic optimization. A well-known class of MC methods is composed of importance sampling (IS) and its adaptive extensions (such as adaptive multiple IS and population MC). In this work... -
21.02.2014 10:15–11:15
HIIT seminar
Exactum B119Title:
MCMC-driven Adaptive Multiple Importance Sampling
Abstract:
Monte Carlo (MC) methods are widely used for statistical inference and stochastic optimization. A well-known class of MC methods is composed of importance sampling (IS) and its adaptive extensions (such as adaptive multiple IS and population MC). In this work, we introduce an iterated batch importance sampler using a population of proposal...
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On competitive recommendations
Jara Uitto, ETH Zürich, Switzerland
Abstract:We are given an unknown binary matrix, where the entries correspond to preferences of users on items. We want to find at least one 1-entry in each row with a minimum number of queries. The number of queries needed heavily depends on the input matrix and a straightforward competitive analysis yields bad results for any online algorithm. Therefore, we analyze our algorithm against a weaker offline algorithm...
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11.02.2014 13:15–14:00
HIIT seminar
Aalto University, Computer Science Building, lecture hall T5Abstract: We are given an unknown binary matrix, where the entries correspond to preferences of users on items. We want to find at least one 1-entry in each row with a minimum number of queries. The number of queries needed heavily depends on the input matrix and a straightforward competitive analysis yields bad results for any online algorithm. Therefore, we analyze our...
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From Lovasz theta to kernel methods: A new connection between graph theory and machine learning
Vinay Jethava, Chalmers University of Technology, Sweden
Abstract:A number of machine learning problems involve analysis of graphs and have borrowed extensively from graph theory - spectral clustering, graph kernels, etc. In this talk, I?ll present our recent work on establishing a connection between Lovasz theta function, a powerful concept in graph theory which has been used heavily in...
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