Sifting through Images with Multinomial Relevance Feedback

Lecturer : 
Dorota Glowacka
Event type: 
HIIT seminar
Event time: 
2011-06-17 10:15 to 11:00
Place: 
Kumpula Exactum C222
Description: 

Talk announcement:
HIIT Seminar Kumpula, Friday June 17 10:15, Exactum C222

Speaker:
Dr Dorota Glowacka
University College London

Title:
Sifting through Images with Multinomial Relevance Feedback

Abstract:

This talk presents the theory, design principles, implementation and
performance results of a content-based image retrieval system based on
multinomial relevance feedback. The system relies on an interactive
search paradigm in which at each round a user is presented with
a set of k images and is required to select one that is closest to
their target. Performance is measured by the number of rounds needed
to identify a specific target image  as well as the the average
distance from the target of the set of k images presented to the
user at each iteration. Results of experiments involving simulations
as well as real users are presented. The conjugate prior Dirichlet
distribution is used to model the problem motivating an algorithm that
trades exploration and exploitation in presenting the images in each
round. A sparse data representation makes the algorithm scalable.
Experimental results show that the new approach compares favourably with
previous work.


Welcome!

HIIT and new Academy of Finland CoE's

Sun, 12.06.2011

Academy of Finland has selected its new 15 Centres of Excellence in Research 2012‒2017. HIIT contributes to three:

Samuel Kaski, Petri Myllymäki, Ilkka Niemelä: Finnish Centre of Excellence in Computational Inference Research

Aapo Hyvärinen: Finnish Centre of Excellence in Inverse Problems Research 

Veli Mäkinen: Finnish Centre of Excellence in Cancer Genetics Research

Congratulations!

 

Negotiated interaction with computers: sensing, inference and multimodal feedback

Lecturer : 
Professor Roderick Murray-Smith
Event type: 
Guest lecture
Event time: 
2011-06-09 13:00 to 14:00
Place: 
E332, Innopoli 2
Description: 

 Abstract: This talk will focus on the 'negotiated interaction' approach to the design of human-computer interaction. This approach incorporates sensing, signal processing, probabilistic inference and multimodal feedback to shape the human-computer interaction loop. I will present examples from the mobile interaction, brain-computer interaction, and music recommendation areas.


Bio: Roderick Murray-Smith is a Professor of Computing Science in the Department of Computing Science at Glasgow University, where he runs the Dynamics and Interaction research group. He works in the overlap between machine learning, interaction design and control theory. Prior to this he has held positions at the Hamilton Institute, NUIM, Technical University of Denmark, M.I.T., and Daimler-Benz Research, Berlin. He works closely with the mobile phone industry, Syntonetic A/s and is a member of Nokia's Scientific Advisory Board.

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

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