MyData 2016

Event type: 
Conference
Event time: 
2016-08-31 09:30 to 2016-09-02 16:00
Place: 
Helsinki House of Culture, Sturenkatu 4
Description: 

 

MyData is an initiative to help people gain more control over their personal data. Let’s shape the future of personal data management together!

The conference brings together engineers, business representatives, researchers, government officials, and civil society activists to discuss the future of personal data management.

Conference venue: Helsinki House of Culture, Sturenkatu 4

Come to MyData 2016 conference to find out!

Organizers: Open Knowledge Finland, Aalto University, Fing

 

Make it Digital!

Lecturer : 
Event type: 
Event
Doctoral dissertation
Respondent: 
Opponent: 
Custos: 
Event time: 
2016-08-18 11:45 to 18:00
Place: 
Aalto University, Otakaari 1M, Espoo
Description: 

Come and hear the latest news about the digitalisation and its untapped opportunities from leading academic and industrial experts. Explore the exhibition and meet StartUps, corporations and organisations on the field of digitalisation. Come and network.

Please register no later than 8 August 2016. The event is free of charge.

Welcome!

See more detailed programme ja registration on event page.

HIIT Kumpula Seminar: SCOT modeling, parallel training and statistical inference

Lecturer : 
Mikhail Malyutov
Event type: 
HIIT seminar
Doctoral dissertation
Respondent: 
Opponent: 
Custos: 
Event time: 
2016-05-27 10:15 to 11:00
Place: 
Exactum B119
Description: 

Abstract:

Stochastic COntext Tree (abbreviated as SCOT) is m-Markov Chain with every state of a string independent of the symbols in its more remote past than the context of length determined by the preceding symbols of this state. SCOT has also appeared in other fields under various names (VLMC, PST, CTW) for compression applications. Consistency of algorithms for training SCOT have been derived for stationary time series with mixing.
We survey recent advances in SCOT modeling, parallel training and statistical inference described in chapter 3 of B. Ryabko, J. Astola and M. Malyutov `Compression-Based Methods of Statistical Analysis and Prediction of Time Series', Springer, which is to appear shortly.

Bio:

Mikhail Malyutov, Professor of Applied Statistics, Northeastern University, Boston. On  his sabbatical he presented talks in many UK and Australian Universities. Before 1995, he was with Kolmogorov Statistical Lab, Moscow.

 

The First Europe-China Workshop on Big Data Management

Event type: 
Workshop
Event time: 
2016-05-16 09:00 to 16:30
Place: 
B222, Exactum, Kumpula Campus
Description: 

Big Data has become ubiquitous in modern society. It challenges state-of-the-art data acquisition, computation and analysis methods. 

This workshop aims to gather experts in big data management to exchange views on cutting-edge data management problems. Further, the workshop aims to create opportunities for strengthening existing collaborations and for establishing new collaborations. Thus, the workshop will allow the attendees to build relations with Chinese and European researchers for future potential grant applications at Horizon 2020, Chinese NSFC, etc.

No registration is needed and welcome to join us! 

The list of speakers and program can be found here

Word Associations as a Language Model for Generative and Creative Tasks

Event type: 
Doctoral dissertation
Doctoral dissertation
Respondent: 
Oskar Gross
Opponent: 
Professor Timo Honkela (University of Helsinki)
Custos: 
Professor Hannu Toivonen (University of Helsinki)
Event time: 
2016-05-06 12:00 to 14:00
Place: 
University of Helsinkin Main Building, Auditorium XIV (Unioninkatu 34, 3rd floor)
Description: 

M.Sc. Oskar Gross will defend his doctoral thesis Word Associations as a Language Model for Generative and Creative Tasks on Friday the 6th of May 2016 at 12 o'clock in the University of Helsinkin Main Building, Auditorium XIV (Unioninkatu 34, 3rd floor). His opponent is Professor Timo Honkela (University of Helsinki) and custor Professor Hannu Toivonen (University of Helsinki). The defence will be held in English.

Word Associations as a Language Model for Generative and Creative Tasks

In order to analyse natural language and gain a better understanding of documents, a common approach is to produce a language model which creates a structured representation of language which could then be used further for analysis or generation. This thesis will focus on a fairly simple language model which looks at word associations which appear together in the same sentence. We will revisit a classic idea of analysing word co-occurrences statistically and propose a simple parameter-free method for extracting common word associations, i.e. associations between words that are often used in the same context (e.g., Batman and Robin). Additionally we propose a method for extracting associations which are specific to a document or a set of documents. The idea behind the method is to take into account the common word associations and highlight such word associations which co-occur in the document unexpectedly often.

We will empirically show that these models can be used in practice at least for three tasks: generation of creative combinations of related words, document summarization, and creating poetry.

First the common word association language model is used for solving tests of creativity -- the Remote Associates test. Then observations of the properties of the model are used further to generate creative combinations of words -- sets of words which are mutually not related, but do share a common related concept.

Document summarization is a task where a system has to produce a short summary of the text with a limited number of words. In this thesis, we will propose a method which will utilise the document-specific associations and basic graph algorithms to produce summaries which give competetive performance on various languages. Also, the document-specific associations are used in order to produce poetry which is related to a certain document or a set of documents. The idea is to use documents as inspiration for generating poems which could potentially be used as commentary to news stories.

Empirical results indicate that both, the common and the document-specific associations, can be used effectively for different applications. This provides us with a simple language model which could be used for different languages.

Availability of the dissertation

An electronic version of the doctoral dissertation is available on the e-thesis site of the University of Helsinki.

 

Printed copies will be available on request from Oskar Gross: oskar.gross@gmail.com.

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