### Department of Mathematics and Systems Analysis

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* Dates within the next 7 days are marked by a star.

Jie Li**An introduction to secure distributed matrix multiplication***** Today * ** Thursday 24 October 2019, 15:15, M3 (M234)

Matrix multiplication is one of the key operations in various engineering applications. A user who has limited computation capability may wish to compute the product of two matrices with the assistance of several distributed servers. However, security becomes an issue when these servers are untrustworthy. In this talk, we focus on information-theoretically secure distributed matrix multiplication with the goal of minimizing the communication overhead.

ANTA Seminar

Jaakko Lehtomaa (University of Helsinki)**On asymptotic independence and support detection techniques for heavy-tailed multivariate data***** ** Monday 28 October 2019, 14:15, Y405

One of the central objectives of modern risk management is to find a set of risks where the probability of multiple simultaneous catastrophic events is negligible. That is, risks are taken only when their joint behavior seems sufficiently independent. Our objective is to provide additional tools for describing dependence structures of multiple risks when the individual risks can obtain very large values.
The study is performed in the setting of multivariate regular variation. We show how asymptotic independence is connected to properties of the support of the angular measure and present an asymptotically consistent estimator of the support. The estimator generalizes to any dimension greater than or equal to two and requires no prior knowledge of the support. The validity of the support estimate can be rigorously tested under mild assumptions by an asymptotically normal test statistic.

Aalto Stochastics and Statistics seminar

Olga Kuznetsova (Aalto University)**What is...Maximum Likelihood Estimation?***** ** Tuesday 29 October 2019, 14:15, M2 (M233)

Maximum Likelihood Estimation (MLE) is a method of estimating a probability distribution by maximising the likelihood function such that the observed data is the most probable. We will discuss the basics of MLE in traditional (parametric) statistics and how this approach has been generalised for non-parametric statistics.

What is...? seminar

Elina Robeva (University of British Columbia)**Maximum Likelihood Estimation of Totally Positive Densities ***** ** Tuesday 29 October 2019, 15:15, U6

Nonparametric density estimation is a challenging problem in theoretical statistics -- in general a maximum likelihood estimate (MLE) does not even exist! Introducing shape constraints allows a path forward. In this talk I will discuss non-parametric density estimation under total positivity (i.e. log-supermodularity) and log-concavity. I will first show that though they possess very special structure, totally positive random variables are quite common in real world data and possess appealing mathematical properties. Given i.i.d. samples from a totally positive distribution, we prove that the maximum likelihood estimator exists with probability one assuming there are at least 3 samples. We characterize the domain of the MLE and show that it is in general larger than the convex hull of the observations. If the observations are 2-dimensional or binary, we show that the logarithm of the MLE is a tent function (i.e. a piecewise linear function) with "poles" at the observations, and we show that a certain convex program can find it. Instead of using a maximum likelihood estimator, we discuss the possibility of using kernel density estimation. This new estimator raises an abundance of theoretical questions.

Department Colloquium

Vito Buffa**Remarks on time-smoothing for parabolic variational problems in metric measure spaces***** ** Wednesday 30 October 2019, 12:15, M3 (M234)

Seminar on analysis and geometry

Niko Lietzén (Aalto)**TBA**

Monday 04 November 2019, 14:15, Y405

Aalto Stochastics and Statistics seminar

Luca Sodomaco (Aalto)**TBA**

Tuesday 05 November 2019, 15:15, M2 (M233)

Timo Takala**Time mollifications in a space-time cylinder (diplomityöesitelmä)**

Tuesday 05 November 2019, 15:15, M3 (M234)

Karl Brustad**TBA**

Wednesday 06 November 2019, 12:15, M3 (M234)

Seminar on analysis and geometry

Nadir Sahllal (Universite Mohammed V de Rabat)**TBA**

Wednesday 06 November 2019, 15:15, M3 (M234)

ANTA Seminar

Hoa Ngo (Aalto)**TBA**

Monday 11 November 2019, 14:15, Y405

Aalto Stochastics and Statistics seminar

Olga Kuznetsova (Aalto)**TBA**

Tuesday 12 November 2019, 15:15, M2 (M233)

Algebra and Discrete Mathematics Seminar

Kari Väisänen**TBA (diplomityöesitelmä)**

Tuesday 12 November 2019, 15:15, M3 (M234)

Julian Weigt**TBA**

Wednesday 13 November 2019, 12:15, M3 (M234)

Seminar on analysis and geometry

Marko Voutilainen (Aalto)**TBA**

Monday 18 November 2019, 14:15, Y405

Aalto Stochastics and Statistics seminar

Laura Jakobsson (Aalto)**TBA**

Tuesday 19 November 2019, 15:15, M2 (M233)

Algebra and Discrete Mathematics Seminar

Cintia Pacchiano**TBA**

Wednesday 20 November 2019, 12:15, M3 (M234)

Seminar on analysis and geometry

Joona Karjalainen (Aalto)**TBA**

Monday 25 November 2019, 14:15, Y405

Aalto Stochastics and Statistics seminar

Prof. Kaisa Nyberg (Aalto University)**TBA**

Tuesday 26 November 2019, 15:15, U6

Department Colloquium

Stavros Evdoridis**Boundary behaviour of harmonic mappings**

Wednesday 27 November 2019, 12:15, M3 (M234)

Seminar on analysis and geometry

Paavo Raittinen (Aalto)**TBA**

Monday 02 December 2019, 14:15, Y405

Aalto Stochastics and Statistics seminar

Muhammad Ardiyansyah (Aalto)**TBA**

Tuesday 03 December 2019, 15:15, M2 (M233)

Algebra and Discrete Mathematics Seminar

Emma-Karoliina Kurki**TBA**

Wednesday 04 December 2019, 12:15, M3 (M234)

Seminar on analysis and geometry

Sami Helander (Aalto)**TBA**

Monday 09 December 2019, 14:15, Y405

Aalto Stochastics and Statistics seminar

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