Signal analysis by stochastic complexity

Lecturer : 
Ciprian Doru Giurcaneanu
Event type: 
HIIT seminar
Event time: 
2011-06-10 10:15 to 11:00
Place: 
Kumpula Exactum C222
Description: 
Talk announcement:
HIIT Seminar Kumpula, Friday June 10 10:15, Exactum C222

Speaker:
Ciprian Doru Giurcaneanu
Tampere University of Technology

Title:
Signal analysis by stochastic complexity

Abstract:
The talk will be focused on the applications of the stochastic
complexity (SC), which has been introduced by Prof. Jorma Rissanen in
the framework of model selection. During recent years, we have proposed
various solutions based on SC for solving the following problems: (1)
Variable selection in Gaussian linear regression; (2) AR order selection
when  the coefficients of the model are estimated with forgetting-factor
least-squares algorithms; (3) Estimation of the number of sine-waves in
Gaussian noise when the sample size is small; (4) Quantifying the
dependence between time series, with applications to the EEG analysis in
a mild epileptic paradigm; (5) Composite hypothesis testing by optimally
distinguishable distributions. During the talk, we will provide a short
overview of the results outlined above by emphasizing the superiority of
SC in comparison with other methods.

Biography:
Ciprian Doru Giurcaneanu received his Ph.D. degree (with honors) from
the Department of Information Technology, Tampere University of
Technology, Finland, in 2001. From 1993 to 1997, he was a Junior
Assistant at ``Politehnica'' University of Bucharest, and since 1997 he
has been with Tampere University of Technology holding various research
positions. He is currently a Research Fellow of the Academy of Finland.
His research is focused on stochastic complexity and its applications.


Welcome!

Optimal Designs for Factorial Experiments with Binary Response

Lecturer : 
Abhyuday Mandal
Event type: 
HIIT seminar
Event time: 
2011-05-27 10:15 to 11:00
Place: 
Kumpula Exactum C222
Description: 
Talk announcement:
HIIT Seminar Kumpula, Friday May 27 10:15, Exactum C222

Speaker:
Abhyuday Mandal
University of Georgia, USA

Title:
Optimal Designs for Factorial Experiments with Binary Response

Abstract: 
We consider the problem of obtaining locally D-optimal designs for
factorial experiments with qualitative factors at two levels each with
binary response and identify optimal allocation of runs for $2^k$ and
$2^{n-k}$ designs. For the $2^2$ factorial experiment with main effects
model we obtain optimal designs analytically in special cases and
demonstrate how to obtain a solution in the general case using cylindrical
algebraic decomposition. The optimal designs are shown to be robust to the
choice of the assumed values of the prior and when there is no basis to
make an informed choice of the assumed values we recommend the use of the
uniform design, i.e., the design that assigns equal number of observations to 
each of the four points. We develop efficient numerical techniques for solving
this very high dimensional optimization problem. For the general $2^k$ case
we show that the uniform design has a maximin property. We also identify
the Bayesian D-optimal designs and compare their performances with locally
D-optimal designs.

Biography: 
Abhyuday Mandal is an assistant professor in the University of
Georgia, USA. He got his Bachelor’s and Master’s degrees in Statistics
from Indian Statistical Institute in Calcutta, India. Then he got another
Master’s degree in Statistics from University of Michigan and Ph.D. degree 
in 2005 from Georgia Institute of Technology, USA. His research interests
are Design of experiments, optimization techniques and genetic algorithms
and fMRI data analysis.


Welcome!
--Matti Järvisalo

DNA codeword design: theory and applications

Lecturer : 
Max H. Garzon
Event type: 
HIIT seminar
Event time: 
2011-05-30 14:30 to 15:15
Place: 
Computer Science Building, Hall T3
Description: 

ICS Forum talk:

            DNA codeword design: theory and applications

                        Prof. Max H. Garzon
                       University of Memphis

Abstract:

Finding large sets of single DNA strands that do not crosshybridize to
themselves or to their complements is an important problem in DNA
computing, self-assembly, DNA memories and phylogenetic analyses,
because of their error correction and prevention properties.  The
problem is in itself NP-complete, even in very simplified versions
using any single reasonable measure that approximates the Gibbs
energy, thus practically excluding the possibility of finding any
efficient procedure to find maximal sets efficiently.  After a quick
survey of advances in this area in the last few years, we focus on a
novel combintorial/geometric framework to analyze this problem.

In this framework, codeword design is reduced to finding large sets of
strands maximally separated in DNA spaces and therefore the size of
such sets depends on the geometry of these DNA spaces.  We present a
new general technique to embed DNA spaces in Euclidean spaces and
thus, among others, reduce the word design problem to the well known
sphere packing problem in information theory.  The embedding sheds
some insights into the geometry of DNA spaces by enabling a
quantitative analysis via well established approximations of the Gibbs
energy, namely the nearest neighbor model of duplex formation.  The
main tool is an efficiently computable combinatorial approximation
which is also a mathematical metric.  As illustration, we briefly show
results of two applications, one to to produce provably nearly optimal
codeword sets (modulo the goodness of the Gibbs energy approximation)
and a new methodology for phylogenetic analyses in Biology.

Assembling and analysing terabases of DNA sequence

Lecturer : 
Richard Durbin
Event type: 
HIIT seminar
Event time: 
2011-05-20 10:15 to 11:00
Place: 
Kumpula Exactum C222
Description: 

Talk announcement:
HIIT Seminar Kumpula, Friday May 20 10:15, Exactum C222

SPEAKER:
Richard Durbin
The Wellcome Trust Sanger Institute

TITLE:
Assembling and analysing terabases of DNA sequence

ABSTRACT:
I will talk about FM-index based approaches to the genome sequence
assembly problem, and/or using Ancestral Recombination Graphs (ARGs) to
efficiently discover genetic variation from population DNA sequence data.

BIO:
*Richard Durbin* is a Senior Group Leader at The Wellcome Trust Sanger
Institute. He is currently co-leading the 1000 Genomes Project to
produce a deep catalogue of human genetic variation by large scale
sequencing using next generation technologies. Previously Richard
contributed to the human genome project, the /C. elegans /genome
sequencing project, and development of the Acedb genome database, the
Pfam and Treefam databases of protein families and the Ensembl genome
data resource. He has also made theoretical and algorithmic
contributions to biological sequence analysis.

Richard has a BA in Mathematics, and a PhD in Biology from Cambridge
University, where he was also a Research Fellow, at King's College, from
1986 to 1988. He was a Fulbright Visiting Scholar in Biophysics at
Harvard University from 1982 to 1983 and a Lucille P Markey visiting
Fellow in the Department of Psychology, Stanford University from 1988 to
1990. He was a staff scientist at the MRC Laboratory of Molecular
Biology from 1990 to 1996, and was Head of Informatics at the Sanger
Institute from 1992-2006 and Deputy Director from 1997 to 2006. He was
elected a Fellow of the Royal Society in 2004.

Richard's home page can be found at
http://www.sanger.ac.uk/research/faculty/rdurbin/


Welcome!
--Matti Järvisalo


HIIT SEMINAR KUMPULA TENTATIVE SCHEDULE Spring 2011
---------------------------------------------------
May 20: Richard Durbin
May 27: Abhyuday Mandal

 

Energy-efficient Trajectory Tracking for Mobile Devices

Lecturer : 
Sourav Bhattacharya
Event type: 
HIIT seminar
Event time: 
2011-05-23 13:15 to 14:00
Place: 
Computer Science Building, Room A328
Description: 

Our next speaker for HIIT Otaniemi seminar series is Sourav Bhattacharya from the "Adaptive Computing" group of the Helsinki Institute for Information Technology HIIT.
 
All ICS@Aalto researchers are also warmly welcome to attend the seminar!
 
HIIT Otaniemi Seminar, Monday May 23, 13:15
Location: Computer Science Building, Room A328
 
Sourav Bhattacharya
Adaptive Computing Group
Helsinki Institute for Information Technology HIIT
Department of Computer Science
University of Helsinki
 
Title:
Energy-efficient Trajectory Tracking for Mobile Devices
 
Abstract:
Emergent location-aware applications often require tracking trajectories of mobile devices over a long period of time. To be useful, the tracking has to be energy-efficient to avoid having a major impact on the battery life of the mobile device. Furthermore, when trajectory information needs to be sent to a remote server, on-device simplification of the trajectories is needed to reduce the amount of data transmission. While there has recently been a lot of work on energy-efficient position tracking, the energy-efficient tracking of trajectories has not been addressed in previous work. In this talk, we introduce a novel on-device sensor management strategy and a set of trajectory updating protocols which intelligently determine when to sample different sensors (accelerometer, compass and GPS) and when data should be simplified and sent to a remote server. The system is configurable with regards to accuracy requirements and provides a unified framework for both position and trajectory tracking. We demonstrate the effectiveness of our approach by emulation experiments on real world data sets collected from different modes of transportation (walking, running, biking and commuting by car) as well as by validating with a real world deployment. The results demonstrate that our approach is able to provide considerable savings in the battery consumption compared to a state-of-the-art position tracking system while at the same time maintaining the accuracy of the resulting trajectory, i.e., support of specific accuracy requirements and different types of applications can be ensured.
 
Welcome! 
 
-- 
Mehmet Gönen
Helsinki Institute for Information Technology HIIT
Department of Information and Computer Science
Aalto University School of Science

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