Tampere International Center for Signal Processing IEEE SP/CAS Chapter of Finland
2010 Workshop on Information Theoretic Methods in Science and Engineering
August 16 - 18, 2010 | Tampere, Finland

Technical Program


Monday, August 16th; Room “Luentosali 1” Sähkötalo building


Registration and Coffee

10:30 – 12:00

Oral session: Information Theoretic Methods

10:30 – 11:00

Maximum mutual information

Jorma Rissanen (Tampere University of Technology)

11:00 – 11:30

Extensions and probabilistic analysis of dynamic model selection

Kenji Yamanishi and Ei-ichi Sakurai (University of Tokyo)

11:30 – 12:00

Cognition beyond Shannon

Flemming Topsøe (University of Copenhagen)

12:00 – 13:30

Lunch at Restaurant Zip, Tietotalo building

13:30 – 14:30

Plenary session: Vincent Poor

Information and inference in the wireless physical layer

Vincent Poor (Princeton University)

14:30 – 15:00

Coffee Break

15:00 – 17:00

Oral session: Information Theoretic Methods

15:00 – 15:30

On the consistency of sequentially normalized least squares

Daniel Schmidt (University of Melbourne) and Teemu Roos (University of Helsinki)

15:30 – 16:00

Thresholding schemes for cepstral analysis

Ciprian Doru Giurcaneanu and Seyed Alireza Razavi (Tampere University of Technology)

16:00 – 16:30

An alternative view of variational Bayes and minimum variational stochastic complexity

Kazuho Watanabe (Nara Institute of Science and Technology)

16:30 – 17:00

A minimum description length method of medium-scale simultaneous inference

David Bickel (University of Ottawa)


Dinner at the Main Building 6th Floor





Tuesday, August 17th; Room “Luentosali 1” Sähkötalo building

9:00 – 10:00

Oral session: Information Theoretic Methods in Engineering

9:00 – 9:30


Quantization of discrete probability distributions

Yuriy Reznik (Qualcomm, US)

9:30 – 10:00


Image reconstruction and the existence of true models

Joseph A. O'Sullivan (Washington University, St. Louis)

10:00 – 10:30

Coffee break

10:30 – 12:00

Oral session: Information Theoretic Methods in Engineering

10:30 – 11:00


Using information theory to study the efficiency and capacity of computers and similar devices

Boris Ryabko (Siberian State University of Telecommunication and Computer Science)

11:00 – 11:30

On mixing models

Tjalling Tjalkens (Technical University of Eindhoven)

11:30 – 12:00

Information theory inspired video coding methods: truth is sometimes better than fiction

Nitin Khanna, Fengqing Zhu, Marc Bosch, Meilin Yang, Mary Comer and Edward J. Delp (Purdue University)

12:00 – 14:00

Lunch at Restaurant Zip, Tietotalo building

14:00 – 15:00

Plenary session: Alon Orlitsky

String reconstruction from substring compositions

Alon Orlitsky (UC San Diego)

15:00 – 15:30


15:30 – 17:30

Oral session: Information Theoretic Methods in Engineering


Maximizing entropy of image models for 2-D constrained coding

S. Forchhammer, M. Danieli, N. Burini, M. Zamarin, and A. Ukhanova (Technical University of Denmark)


Cooperative sensing policies for identification and exploitation of underutilized radio spectrum

Visa Koivunen (Aalto University)


Error-correcting decision diagrams

Helena Astola, Stanislav Stankovic, Jaakko T. Astola  (Tampere University of Technology)


Phase retrieval from multiple plane observations: constrained variational formulation and augmented Lagrangian recursive algorithm

Artem Migukin, Vladimir Katkovnik, and Jaakko Astola (Tampere University of Technology)


Dinner at Restaurant Zip, Tietotalo building






Wednesday, August 18th; Room “Luentosali 1” Sähkötalo building

9:00 – 10:00

Plenary session: Marcelo Weinberger

Tree models revisited

Marcelo Weinberger (Hewlett-Packard Laboratories, US)

10:00 – 10:30

Coffee break

10:30 – 12:30

Special session: Information Theoretic Methods in Statistics

10:30 – 10:50

On maximal likelihood estimators of the shape parameter when the scale parameter is nuisance

Alexander Zaigrajew (University of Torun, Poland) 

10:50 – 11:10

A comparison of WALS estimation with pretest and model selection alternatives with an application  to cost-effectiveness of hip fracture treatments

Antti Liski (Tampere University of Technology), Erkki P. Liski (University of Tampere), Reijo Sund and Merja Juntunen  (National Institute for Health and Welfare)

11:10 – 11:30

Analyzing microarray data via random forest

Daniel Fischer (University of Tampere and TU Dortmund)

11:30 – 11:50

Minimum description length based hidden Markov model clustering for life sequence analysis

Jouni Helske(Tampere University of Technology), Mervi Eerola (University of Jyväskylä), Ioan Tabus (Tampere University of Technology)

11:50 – 12:10

Stochastic prediction optimality

Sami Helle (University of Tampere)

12:10 – 13:30

Lunch at Restaurant Zip, Tietotalo building

13:30 – 15:10

Oral session: Information Theoretic Methods in Engineering

13:30 – 13:50

Evaluation of marine windspeed derived from SAR imagery based on buoy observations

Alexander Komarov, Vladimir Zabeline, Mikhail Malioutov, and Christopher Boulay (Northeastern University)

13:50 – 14:10

Hidden Markov models for induction of morphological structure of natural language

Hannes Wettig, Suvi Hiltunen, Roman Yangarber (University of Helsinki)

14:10 – 14:30

Image deblurring by augmented Lagrangian with BM3D frame prior

Aram Danielyan, Vladimir Katkovnik and Karen Egiazarian (Tampere University of Technology)

14:30 – 14:50

Code lengths for model classes with continuous uniform distributions

Panu Luosto (University of Helsinki)

14:50 – 15:10

Secrecy rate region in the interference channel with common information

Hamid G. Bafghi (Shahed University, Tehran), Somayeh Salimi (Sharif University of Technology, Tehran), Babak Seyfe (Shahed University, Tehran), and Mohammad R. Aref (Sharif University of Technology, Tehran)

15:20 – 21:30

Free discussions, sauna, and dinner at Restaurant Maisa by Näsijärvi lake


Bus leaves from the parking lot in front of Tietotalo building, Entrance 1

15:50 – 18:30

Free discussions and sauna

18:30 – 21:00


21:00 – 21:30

Bus transportation to Tampere





H. Vincent Poor, Princeton University

Information and Inference in the Wireless Physical Layer

Abstract:  Wireless networking applications continue to motivate challenging problems in information theory, signal processing, and other fields. A salient feature of wireless networks is the close interaction between the physical layer and the other networking layers. This phenomenon is a result of the principal distinguishing features of wireless, namely mobility and the importance of physical properties (diffusion, interference, fading and radio geometry) in determining link characteristics. For example, the applications layer interacts considerably with the physical layer, as is well known through the importance of quality-of-service in wireless network design. This talk will explore briefly four research areas, primarily involving information theoretic or inferential problems, each of which is motivated by an applications-layer issue. In particular, the four applications of file transfer, inference, real-time multimedia transmission, and social networking, will be used to motivate consideration of four respective research problems involving the physical layer: physical layer security in data networks, distributed inference in sensor networks, finite-blocklength capacity in multimedia networks, and connectivity in small-world networks. Recent progress in each of these four research areas will be reviewed.

Bio: H. Vincent Poor is with Princeton University, where he is the Michael Henry Strater University Professor of Electrical Engineering and Dean of the School of Engineering and Applied Science.  His current research interests are in the areas of stochastic analysis, statistical signal processing, and information theory, and their applications in wireless networking and related fields. His publications in these areas include the recent books MIMO Wireless Communications (Cambridge, 2007), Quickest Detection (Cambridge, 2009), and Information Theoretic Security (Now, 2009).  Dr. Poor is a Fellow of the IEEE, a member of the U. S. National Academy of Engineering, a Fellow of the American Academy of Arts & Sciences, and an International Fellow of the U. K. Royal Academy of Engineering. Recent recognition of his work includes the 2009 Edwin Howard Armstrong Achievement Award of the IEEE Communications Society.




Alon Orlitsky, University of California, San Diego 

String Reconstruction from Substring Compositions

Abstract: Motivated by mass-spectrometry protein sequencing, we consider a simply-stated problem of reconstructing a string from the multiset of its substring compositions. We show that all strings of length 7,one less than a prime, or one less than twice a prime, can be reconstructed. For all other lengths we show that reconstruction is not always possible and provide sometimes-tight bounds on the largest number of strings with given substring compositions. The lower bounds are derived via combinatorial arguments and the upper bounds are obtained from algebraic considerations that precisely characterize the set of strings with the same substring compositions in terms of the factorization of biariate polynomials. The problem can be viewed as a combinatorial simplification of the turnpike problem, and its solution may shed light on this long-standing problem as well. Joint work with Jayadev Acharya, Hirakendu Das, Olgica Milenkovic, and Shengjun Pan.


Bio: Alon Orlitsky received B.Sc. degrees in Mathematics and Electrical Engineering from Ben Gurion University in 1980 and 1981, and M.Sc. and Ph.D. degrees in Electrical Engineering from Stanford University in 1982 and 1986.

From 1986 to 1996 he was with the Communications Analysis Research Department of Bell Laboratories. He spent the following year as a quantitative analyst at D.E. Shaw and Company, an investment firm in New York city. In 1997 he joined the University of California, San Diego, where he is currently a professor of Electrical and Computer Engineering and of Computer Science and Engineering, and directs the Information Theory and Applications Center.

Alon's research concerns information theory, statistical modeling, machine learning, and speech recognition. He is a recipient of the 1981 ITT International Fellowship and the 1992 IEEE W.R.G. Baker Paper Award, a co-recipient of the 2006 Information Theory Society Paper Award, a fellow of the IEEE, and holds the Qualcomm Chair for Information Theory and its Applications at UCSD.




Marcelo J. Weinberger, Hewlett-Packard Laboratories, Palo Alto, California

Tree models revisited

Abstract:  Tree models have been extensively studied, as valuable tools in data compression and other applications in information theory and statistics. Efficient algorithms exist for their estimation, as well as for universal compression of data relative to this model class. After a review of classical results on tree models, we will discuss some less known aspects of their behavior that were the subject of more recent research and that shed light on their structure. We will also discuss recent generalizations to multi-tracked data.

 Bio: Marcelo J. Weinberger received the Electrical Engineer degree from the Universidad de la República, Montevideo, Uruguay, in 1983, and the M.Sc. and D.Sc. degrees from Technion -- Israel
Institute of Technology, Haifa, Israel, in 1987 and 1991, respectively, both in electrical engineering. Since 1993 he has been with Hewlett--Packard Laboratories, Palo Alto, California, where he is a Distinguished Scientist and leads the Information Theory Research group. His research interests include source coding, sequential decision problems, statistical modeling, and image compression.

Dr. Weinberger is a coauthor of the algorithm at the core of the JPEG-LS lossless image compression standard, and also contributed to the coding algorithm of the JPEG2000 image compression standard. He is an IEEE Fellow and a corecipient of the 2006 IEEE ComSoc & Information Theory Joint Paper Award.


Last updated: Tuesday, August 10, 2010