Browsing by Author "Parviainen, Pekka"

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  • Distributed Bayesian matrix factorization with limited communication
    (2019-01-01) Qin, Xiangju; Blomstedt, Paul; Leppäaho, Eemeli; Parviainen, Pekka; Kaski, Samuel
     A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
    Bayesian matrix factorization (BMF) is a powerful tool for producing low-rank representations of matrices and for predicting missing values and providing confidence intervals. Scaling up the posterior inference for massive-scale matrices is challenging and requires distributing both data and computation over many workers, making communication the main computational bottleneck. Embarrassingly parallel inference would remove the communication needed, by using completely independent computations on different data subsets, but it suffers from the inherent unidentifiability of BMF solutions. We introduce a hierarchical decomposition of the joint posterior distribution, which couples the subset inferences, allowing for embarrassingly parallel computations in a sequence of at most three stages. Using an efficient approximate implementation, we show improvements empirically on both real and simulated data. Our distributed approach is able to achieve a speed-up of almost an order of magnitude over the full posterior, with a negligible effect on predictive accuracy. Our method outperforms state-of-the-art embarrassingly parallel MCMC methods in accuracy, and achieves results competitive to other available distributed and parallel implementations of BMF.
  • Distributed Bayesian matrix factorization with limited communication
    (2019-10-01) Qin, Xiangju; Blomstedt, Paul; Leppäaho, Eemeli; Parviainen, Pekka; Kaski, Samuel
     A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
    Bayesian matrix factorization (BMF) is a powerful tool for producing low-rank representations of matrices and for predicting missing values and providing confidence intervals. Scaling up the posterior inference for massive-scale matrices is challenging and requires distributing both data and computation over many workers, making communication the main computational bottleneck. Embarrassingly parallel inference would remove the communication needed, by using completely independent computations on different data subsets, but it suffers from the inherent unidentifiability of BMF solutions. We introduce a hierarchical decomposition of the joint posterior distribution, which couples the subset inferences, allowing for embarrassingly parallel computations in a sequence of at most three stages. Using an efficient approximate implementation, we show improvements empirically on both real and simulated data. Our distributed approach is able to achieve a speed-up of almost an order of magnitude over the full posterior, with a negligible effect on predictive accuracy. Our method outperforms state-of-the-art embarrassingly parallel MCMC methods in accuracy, and achieves results competitive to other available distributed and parallel implementations of BMF.
  • Julkisen vienninedistämisen vaikuttavuuden mittaaminen kansainvälisessä tutkimuksessa
    (2002) Parviainen, Pekka
     School of Business | Master's thesis
  • Kauppamatkustajan ongelma
    (2016-04-17) Oksanen, Ilkka
     Perustieteiden korkeakoulu | Bachelor's thesis
  • Structure discovery in Bayesian networks by sampling partial orders
    (2016-04-01) Niinimäki, Teppo; Parviainen, Pekka; Koivisto, Mikko
     A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
    We present methods based on Metropolis-coupled Markov chain Monte Carlo (MC3) and annealed importance sampling (AIS) for estimating the posterior distribution of Bayesian networks. The methods draw samples from an appropriate distribution of partial orders on the nodes, continued by sampling directed acyclic graphs (DAGs) conditionally on the sampled partial orders. We show that the computations needed for the sampling algorithms are feasible as long as the encountered partial orders have relatively few down-sets. While the algorithms assume suitable modularity properties of the priors, arbitrary priors can be handled by dividing the importance weight of each sampled DAG by the number of topological sorts it has - we give a practical dynamic programming algorithm to compute these numbers. Our empirical results demonstrate that the presented partial-order-based samplers are superior to previous Markov chain Monte Carlo methods, which sample DAGs either directly or via linear orders on the nodes. The results also suggest that the convergence rate of the estimators based on AIS are competitive to those of MC3. Thus AIS is the preferred method, as it enables easier large-scale parallelization and, in addition, supplies good probabilistic lower bound guarantees for the marginal likelihood of the model.
  • Syövän etenemisen laskennallinen mallintaminen
    (2014-12-15) Nzau, Makenzi
     Sähkötekniikan korkeakoulu | Bachelor's thesis
  • Syövän etenemisen laskennalliset mallit
    (2016-04-17) Vahermaa, Vesa
     Perustieteiden korkeakoulu | Bachelor's thesis
  • Temperament clusters in a normal population: Implications for health and disease
    (2012-07-18) Wessman, Jaana; Schönauer, Stefan; Miettunen, Jouko; Turunen, Hannu; Parviainen, Pekka; Seppänen, Jouni K.; Congdon, Eliza; Service, Susan; Koiranen, Markku; Ekelund, Jesper; Laitinen, Jaana; Taanila, Anja; Tammelin, Tuija; Hintsanen, Mirka; Pulkki-Råback, Laura; Keltikangas-Järvinen, Liisa; Viikari, Jorma; Raitakari, Olli T; Joukamaa, Matti; Järvelin, Marjo-Riitta; Freimer, Nelson; Peltonen, Leena; Veijola, Juha; Mannila, Heikki; Paunio, Tiina
     A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
    Background: The object of this study was to identify temperament patterns in the Finnish population, and to determine the relationship between these profiles and life habits, socioeconomic status, and health. Methods/Principal Findings: A cluster analysis of the Temperament and Character Inventory subscales was performed on 3,761 individuals from the Northern Finland Birth Cohort 1966 and replicated on 2,097 individuals from the Cardiovascular Risk in Young Finns study. Clusters were formed using the k-means method and their relationship with 115 variables from the areas of life habits, socioeconomic status and health was examined. Results: Four clusters were identified for both genders. Individuals from Cluster I are characterized by high persistence, low extravagance and disorderliness. They have healthy life habits, and lowest scores in most of the measures for psychiatric disorders. Cluster II individuals are characterized by low harm avoidance and high novelty seeking. They report the best physical capacity and highest level of income, but also high rate of divorce, smoking, and alcohol consumption. Individuals from Cluster III are not characterized by any extreme characteristic. Individuals from Cluster IV are characterized by high levels of harm avoidance, low levels of exploratory excitability and attachment, and score the lowest in most measures of health and well-being. Conclusions: This study shows that the temperament subscales do not distribute randomly but have an endogenous structure, and that these patterns have strong associations to health, life events, and well-being.
  • Video transmission on TETRA Enhanced Data Service platform
    (2008) Vehkalahti, Vesa
     Helsinki University of Technology | Master's thesis
    Puheviestintä on laajasti käytetty palvelu yleisen turvallisuuden ja kriisinhallinnan tarpeisiin, mutta tarve digitaalisen videon hyödyntämiselle on herännyt, koska se tarjoaa uusia mahdollisuuksia missio-kriittiseen kommunikointiin hätätilanteissa. TETRA Enhanced Data Service (TEDS) on nykyaikaisinta mobiilitekniikkaa, joka mahdollistaa nopean pakettidatan ja sen ansiosta myös reaaliaikaisen videon siirron. Koska TEDS:n tarjoama siirtokaista on rajallinen, tämä asettaa haasteita videokoodekkien pakkaustehokkuudelle ja koodausominaisuuksille. Bittinopeus, resoluutio ja kuvanopeus ovat olennaisia parametreja, jotka vaikuttavat videon laatuun ja määrittelevät siirtokaistan tarpeen videon siirron aikana. Tämän diplomityön tarkoituksena on tutkia videon laatua ja toimivuutta sekä kokonaisvideoviivettä reaaliaikaisen videon siirron aikana Ensiksi viiden valitun videokoodekin suorituskykyä ja videon laatua mitataan kattavasti 125 kbps:n rajoitetulla siirtokaistalla, jonka tarkoituksena on emuloida TETRA/TEDS systeemin tavanomaista siirtonopeutta. Toiseksi videota siirretään TEDS prototyypin yli. Videomittauksien tulokset osoittivat H.264:n olevan TEDS:lle soveltuva videokoodekki, koska se pystyi tarjoamaan muita testattuja videokoodekkeja parempaa videon laatua ja pienempää kokonaisvideoviivettä, ja pystyi toimimaan alhaisemmalla ja tasaisemmalla bittinopeudella. Yhteyden laadun vaihtelu ja hetkellisesti riittämätön siirtonopeus aiheuttivat merkittävää videon laadun heikkenemistä videon siirron aikana.