Centre for Advanced Research in Applied Mathematics and Statistics, MAHE, Manipal, India
The purpose of International Workshop on Matrices and Statistics is to foster, in an informal setting, the interaction of researchers in the interface between Matrix Theory and Statistics.
The 28th International Workshop on Matrices and Statistics, IWMS 2021, will be held during the period December 13-15, 2021 at the Centre for Advanced Research for Applied Mathematics and Statistics, Manipal Academy of Higher Education, (MAHE) Manipal, Karnataka, India.
The theme of the workshop shall focus on the theory and applications of the following topics in different branches of science such as Biology, Computer and Information Science, Economics, Electronics, Genetics, Office Statistics, Social Statistics and Accountancy:
On behalf of the International Organizing Committee, Scientific Committee, and the Local Organizing Committee we have much pleasure in extending a cordial invitation to participate this workshop.
This series of Workshops has a long history, see https://www.sis.uta.fi/tilasto/iwms/IWMS-history.pdf and we welcome the opportunity to hold the workshop once again in India. The 9th Workshop was held at Hyderabad in 2000, celebrating 80th birthday of Calyampudi Radhakrishna Rao, popularly known as C. R. Rao. The present 28th IWMS will be held beside ICLAA 2021, the common day between IWMS and ICLAA, December 15, 2021, will have some common sessions in honor of Prof. Calyampudi Radhakrishna Rao. We are sure that 28th IWMS will be a great success with the participation of prominent researchers from across the globe working in Statistics, Matrix Theory and allied subjects.
The purpose of the Workshop is to stimulate research and, in an informal setting, to foster the interaction of researchers in the interface between statistics and matrix theory. The Workshop will provide a forum through which statisticians may be better informed of the latest developments and newest techniques in linear algebra and matrix theory and may exchange ideas with researchers from a wide variety of countries.
As well as range of plenary speakers we are to strengthening the interactions between participants by organizing a range of minisymposia in various specialist areas. Beside organizing invited talks from eminent speakers, we invite participants to submit their research articles in the sessions of contributory talks.
We intend to publish a special issue dedicated to the conferences ALAPS 2020, IWMS 2021, and ICLAA 2021 in a reputed journal. We thank ‘AKCE International Journal of Graphs and Combinatorics’ for its consent for publishing a special issue with the articles focused on common area of interest of the journal and conferences.
Guest editorial team invites research articles in the following mentioned focus area for the possible publication in the special issue dedicated to the conferences. Article need not be the one presented in the ALAPS 2020/ IWMS 2021/ ICLAA 2021 and similarly author need not be among speakers or participants of ALAPS 2020/ IWMS 2021/ ICLAA 2021, though we encourage the speakers to submit an article presented in the conference.
Focus Area of Special Issue: Keeping in view of focus area of journal and conference, the articles submitted are expected to be in the following broad area:
Guest Editors Team: Consists Scientific Advisory Committee (SAC) members
associated with
Journal: AKCE International Journal of Graphs and Combinatorics (An open access journal)
Web Link: https://www.tandfonline.com/loi/uakc20.
Publisher: Taylor & Francis online
How to Submit: Author may submit an article with in focus area mentioned above, directly to the convener of SAC, who is the coordinator for the special issue and the proceedings ( km.prasad@manipal.edu; kmprasad63@gmail.com) with the suggestion of a guest editor to handle the paper.
Formatting: Author may refer to instructions for authors on the journal site with the link: https://www.tandfonline.com/action/authorSubmission?show=instructions&journalCode=uakc20
Submission fee & APC: There is no Submission Fee or Article Processing Charges (APC) for the articles submitted for the special issue.
Review Process
Important Dates
Receiving the articles: April 30, 2022
Completing the review process including necessary revision: September 30, 2022
Submitting the final manuscript in the necessary format: October 31, 2022
Publication of special issue: January 31, 2023 (subject to convenience of AKCE Journal)
This volume is to cherish the beautiful path laid by the living legend
who completed 100 years of fruitful life in 2020 and in memories of young and dynamic
whom we missed in this year of 2021.
The proceedings proposal has been submitted to SPRINGER for the possible publication in a scopus indexed series.
Research articles in detail and expository articles are invited for the possible publication in the volume of proceedings in the focus area of ALAPS 2020, IWMS 2021, ICLAA 2021 and the work by Professor Rao. Though we appreciate the submission of work presented in any of these connected conferences, we also invite any good articles in the form of chapters which throw more light on the work of Professor Rao and help young scholars to understand Rao’s work and further advancements. We welcome articles in memory of Arbind Lal.
Editorial Team
Nature of article
We appreciate articles of following nature:
Timeline
Last Date for receiving the articles: April 30, 2022
Completion of Review, including necessary revision: October 31, 2022
Proof reading & Pre-production work by SPRINGER: December 31, 2022
Publication of edited volume: March 31, 2023
Number of pages
We appreciate the number of pages of article restricted to 20-25, but in some exceptional cases it could be more.
Title : A further introduction to Philatelic Lattice Grids (PLGs) with four-sided stamps
(First International Mini-Symposium on Mathematical Philately)
Organizer : George PH Styan (McGill University, Canada)
Confirmed Speakers:
Title : Statistics and Big data: A Research Paradigm Shift
Organizer : Samir K. Neogy (ISI, Delhi, India)
Confirmed Speakers:
International Organizing Committee – IWMS 2021
Previous IWMS
We do hope, we have an opportunity to meet in Manipal and enjoy the academic deliberation.
Simo Puntanen (Finland)
Chair, International Organizing Committee
28th International Workshop on Matrices and Statistics
Ravindra B Bapat
Chair, Scientific Committee
ICLAA 2021 & IWMS 2021
Narayana Sabhahit (Registrar, MAHE)
Chair, Local Organizing Committee
ICLAA 2021 & IWMS 2021
Category | IWMS 2021 / ICLAA 2021 / IWMS 2021 + ICLAA 2021 |
---|---|
Foreign Nationals | $100 |
Indian Nationals, Research Scholars, Faculty and students | ₹1000+GST |
Category | IWMS 2021 / ICLAA 2021 | IWMS 2021 + ICLAA 2021 |
---|---|---|
Foreign Nationals | $350 | $350 |
Indian Nationals, Research Scholars and Faculty | ₹2000+GST | ₹3500+GST |
Indian Students having no funding support | ₹1000+GST | ₹2000+GST |
Category | IWMS 2021 / ICLAA 2021 | IWMS 2021 + ICLAA 2021 |
---|---|---|
Foreign Nationals | $200 | $200 |
Indian Nationals, Research Scholars and Faculty | ₹1000+GST | ₹2000+GST |
The following are prevailing COVID protocols (as of November 23, 2021) to be followed at the MAHE Campus. At the time of the beginning of conferences, the protocol may change subject to the situation. Delegates coming from outstation are required to note the same.
Wish to see you at Manipal!!
Research Interests:
Ordered data analysis, Uni-variate and multivariate distribution theory, Reliability theory, Survival analysis, Applied probability, Stochastic orderings, Non-parametric statistics,… Read more
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Professor N. Balakrishnan is a Distinguished University Professor at McMaster University, Hamilton, Ontario, Canada. He completed his PhD… Read more
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Mathematics: Convexity and Inequalities, Matrix Theory. Optimization Theory: Nonsmooth Analysis, Symbolic Computation. Applied Mathematics: Numerical Linear Algebra, Linear… Read more
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Adi Ben-Israel received his PhD from Northwestern University, United States (1962). He has published over 5 books in… Read more
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Matrices, Graphs and the connections between the two Read more
Achievements:
Abraham Berman received his B.Sc. (1966) and M.Sc. (1968) in mathematics from the Technion. In 1970 he received… Read more
Let $S$ be a set of nonnegative numbers. A matrix $A$ is completely positive over $S$ if it can be decomposed as $A=BB^T$, where the entries of $B$ are in $S$. The talk is a survey of results on completely positivity over $S$ in the cases $S=R,\;S=Q\; S=Z$ and $S=\{0,1\}$.
Research Interests:
Economics: Information economics, Moral hazard problems and incentives. Econometrics: Large dimensional time series, Resampling in time series, Asymptotics… Read more
Achievements:
Professor completed his M. Stat. (1980) and PhD (1987) from the Indian Statistical Institute. He has been an… Read more
Research Interests:
Magic Squares, Latin squares, Philatelic Latin squares, Magic card puzzles Read more
Achievements:
Garry Ka Lok Chu has been teaching at Dawson College for more than a decade. He works as… Read more
Research Interests:
Methodological: Bioinformatics, Clustering and Classification, Genomics, Proteomics, Infectious Disease Modeling, Non-linear Regression modeling for Systems Biology, Statistical Issues… Read more
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Susmita Datta has received her PhD degree in Statistics from the University of Georgia, Athens, Georgia, USA followed… Read more
Transcriptomic studies such as in bulk RNA-sequencing, one can examine transcript abundance measurements averaged over bulk populations of thousands (or even millions) of cells. While these measurements have been valuable in countless studies, they often conceal cell-specific heterogeneity in expression signals that may be paramount to new biological findings. Fortunately, with single cell RNA-sequencing (scRNA-Seq), transcriptome data from individual cells are now accessible, providing opportunities to investigate functional states of cells, identify rare cell populations and uncover diverse gene expression patterns in cell populations that seemed homogeneous. Most importantly it provides an unprecedented resolution to the characterization of cellular clinical isolates. However, there are challenges analyzing such scRNA-Seq data. Amongst many challenges the most significant are the bimodal or multimodal distribution, sparsity and tremendous heterogeneity in the data. Consequently, we will describe potential ways of statistical modeling of such data, finding differentially expressed genes and methods for constructing gene-gene interaction network using this data.
Research Interests:
Experimental designs, Optimality of designs under univariate and multivariate linear models, Optimization of some specific functions of eigenvalues… Read more
Achievements:
Dr. Katarzyna Filipiak in the department of Mathematical and Statistical Methods, Poznan University of Life Sciences. She obtained… Read more
The problem of measuring discrepancy of a given matrix from structured one often arises in statistics. In this talk the properties of the Frobenius norm, entropy and quadratic loss functions will be compared in the context of power of the test.
Research Interests:
Mathematical Statistics, Medicine, Health Sciences, Psychology, Human Development, Political Science, History, the Humanities, Social Sciences, Zoology, Botany, Marine… Read more
Achievements:
Stephen J. Haslett is a former Professor and Director of the Statistical Consulting Unit. He is a Fellow… Read more
The general condition for the BLUEs in a linear model being unaltered by a change in error covariance structure is due to C.R Rao (1971). This condition can be written so that the entire term that can be added to the original covariance is block diagonal in form. When the original full linear model is made smaller by reducing the number of regressors, block diagonal matrices for the quadratic form based on the matrix orthogonal to the design matrix also provide insight into conditions for full, small and intermediate models having the same BLUEs for all the parameters they share. Haslett et al (2020) also consider properties of BLUEs in full versus small linear models with new observations where the supplementary quadratic form to the original covariance structure again involves block diagonal matrices, but based instead on the design matrix. Common themes will be explored using block diagonal matrices and the partitions they imply. Extension to linear mixed models and BLUPs is possible.
Research Interests:
Machine learning, Artificial intelligence, Feature selection, representation learning, rough sets Read more
Achievements:
Andrzej Janusz is an active and experienced researcher in the fields of science related to data exploration, machine… Read more
Active learning is a subfield of machine learning that considers interactive algorithms for training prediction models. In such a setup, the learner can iteratively query an oracle to obtain labels for a limited number of instances from a large volume of available data. This approach is particularly useful in practical applications when the label acquisition is time-consuming or expensive. During my talk, I will explain how we deal with such applications at QED Software. As an example, I will use one of our recent projects in which we are working on a model for the identification of critical turns (so-called, game-changers) in a multiplayer video game called Tactical Troops: Anthracite Shift. I will describe the main steps in the active learning cycle, and discuss the most common practical issues related to the deployment of successful active learning systems.
Research Interests:
Microeconomic Theory, Individual and Social (Group) Choice (Decision Making) Theory, Game Theory Read more
Achievements:
Professor Lahiri is currently a Professor of Economics at the School of Petroleum Management, PD Energy University. His… Read more
In this paper, we introduce the class of quadratically optimal (bimatrix) games, which are bi-matrix games whose set of equilibrium points contain all pairs of probability vectors which maximize the expected pay-off of some pay-off matrix. We call the equilibrium points obtained in this way, quadratically optimal equilibrium points. We prove the existence of quadratically optimal equilibrium points of identical bi-matrix games, i.e. bi-matrix games for which the two pay-off matrices are equal, from which it easily follows that weakly potential bi-matrix games (a generalization of potential bi-matrix games) are quadratically optimal. We also show that those weakly potential square bi-matrix games which have potential matrices that are two-way matrices are quadratically and symmetrically solvable games, i.e., there exists a square pay-off matrix whose expected pay-off maximizing probability vectors subject to the two probability vectors (row probability vector and column probability vector) being equal, are equilibrium points of the bi-matrix game. None of our results require using a fixed point theorem argument in the proofs. We show by means of an example of a 2×2 identical symmetric potential bi-matrix game that for every potential matrix of the game, the set of pairs of probability distributions that maximizes the expected pay-off of the potential matrix is a strict subset of the set of equilibrium points of the potential game.
Research Interests:
Matrices, Matrix Theory, Algebra, Linear Algebra, Statistics, Applied Mathematics, Maximum Likelihood, Linear Regression, Pure Mathematics, Regression Modeling, Linear… Read more
Achievements:
Augustyn Markiewicz completed his MS in Mathematics in 1980 at Adam Mickiewicz University, Poznań and received Ph.D in… Read more
The need for estimation of covariance matrix with a given structure arises in various multivariate models. We are studying this problem for linear structures. The commonly used maximum likelihood estimation method is in general complex and time consuming when restricted to structured and positively definite matrices; cf. [K. Filipiak, M. John, A. Markiewicz, 2020]. Therefore we consider some alternatives to the maximum likelihood estimation based on approximation of the unstructured sample covariance matrix by structured, positive definite matrices. The approximation via Frobenius as well entropy loss functions turn out to be numerically ineffective; cf. [K. Filipiak, A. Markiewicz, A. Mieldzioc, A. Sawikowska, 2018] and [M. Janiszewska, A. Markiewicz, M. Mokrzycka, 2020]. Instead, we propose a much more numerically efficient method of projecting the unstructured sample covariance matrix on a given linear structure (cf. [M. Ohlson, D. von Rosen, 2010]) and then, if necessary, restoring its definiteness by a specific shrinkage method. The statistical properties of these estimators and maximum likelihood estimators are compared via simulation study.
Research Interests:
Applied Statistics, Linear Programming, Nonlinear Programming, Non-cooperative games, Stochastic games, Statistical Quality Control, Six Sigma, Quality Management. Read more
Achievements:
Based on his research and teaching interests, in applied statistics and matrix methods, he has published several research… Read more
More and more data are being produced today by an increasing number of electronic devices physically surrounding us and on the internet. The large amount of data and the high frequency at which they are produced have resulted in the introduction of the term ‘Big Data’. Today, in sectors like social development, healthcare, education, energy, governance etc have more data than they can handle, and recognize the potential for value, but the promise of big data still has not been realized, according to the leading academic and business media sources. Big data has caused the scientific community to re-examine its methodology of scientific research. Big data technologies and the corresponding fundamental research have become a research focus in academia. An emerging interdisciplinary discipline called data science has been gradually coming into place. This takes big data as its research object and aims at generalizing the extraction of knowledge from data. In fact we also need new approaches in statistics and computer science to analyze Big Data.
Research Interests:
Matrix methods in statistics, Generalized inverses, Canonical correlations Read more
Achievements:
He was a Senior Researcher of the Academy of Finland in 1992--1995. His main research interest lies on… Read more
We consider the general linear model $y = X \beta + \varepsilon$ supplemented with the new unobservable random vector $ y_{*}$,coming from $ y_{*} = X_{*}\beta + \varepsilon_{*}$, where the covariance matrix of $y_{*}$ is known as well as the cross-covariance matrix between $y_{*}$ and $y$. A linear statistic $F y$ is called linearly sufficient for $X_{*} \beta$ if there exists a matrix $A$ such that $A F y$ is the best linear unbiased estimator, BLUE, for $X_{*} \beta$. The concept of linear sufficiency with respect to a predictable random vector is defined in the corresponding way but considering the best linear unbiased predictor, BLUP, instead of BLUE. In this paper, we consider the linear sufficiency of $F y$ with respect to $ y_{*}$, $X_{*} \beta$, and $\varepsilon_{*}$.
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Developing mathematical and probabilistic methods and models, for example, harmonic analysis, ODE/PDE, Stochastic Processes etc. Methodologies in Machine… Read more
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Dr. Rao is a Professor, Director at the Laboratory for Theory and Mathematical Modeling, Medical College of Georgia,… Read more
Through this talk, a new method introduced by the author, called, exact deep learning machines (EDLM) will be introduced. Such methods will be compared with traditional artificial intelligence (AI) techniques. How the EDLMs provide better alternatives for AI-related experiments will be discussed. The difference of approaches of deep learning versus AI through two theoretical examples will be provided.
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Multivariate Analysis, Probability and Statistics, Regression Analysis, Mathematical Statistics and its applications Read more
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He received a PhD from Stockholm University (1986). He was adviser for 18 undergraduate (master) theses in Mathematical… Read more
Some techniques to decompose linear and bilinear spaces are presented. The techniques are applied to the treatment of the Gauss-Markov model, linear equations, bilinear models, partial least squares (PLS) and reduced rank regression models. In particular for some of the models residuals will be considered.
Research Interests:
Percolation Theory & Random Graphs, Extreme Value Theory Read more
Achievements:
Anish Sarkar is an Associate Professor in Stat-Math Unit, at Indian Statistical Institute, Delhi Centre. He obtained his… Read more
Hack (1957) while studying the drainage system in the Shenandoah valley and the adjacent mountains of Virginia, observed a power law relation $l \sim a^{0.6}$ between the length $l$ of a stream from its source to a divide and the area $a$ of the basin that collects the precipitation contributing to the stream as tributaries. We study the tributary structure of Howard’s drainage network model of headward growth and branching studied earlier by Gangopadhyay, Roy and Sarkar (2004). We show that the exponent of Hack’s law is $2/3$ for Howard’s model. Our study is based on a scaling of the process whereby the limit of the watershed area of a stream is area of a Brownian excursion process. To obtain this, we define a dual of the model and show that under diffusive scaling, both the original network and its dual converge jointly to the standard Brownian web and its dual.
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Medical image analysis, Image reconstruction, Filter bank theory, Computational photography, Light field and Optimization techniques Read more
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He completed his PhD in IIT, Kanpur (2001). He has been a Member Technical Staff at Siemens Research… Read more
Research Interests:
Multivariate Statistics, Growth Curve model with a linearly structured covariance matrix, Kronecker structured covariance matrix Read more
Achievements:
Martin Singull is a Professor, Head of Division of Mathematical Statistics at the Department of Mathematics, Linkoping University.… Read more
In both univariate and multivariate analysis, residuals are used for model diagnostics. In this presentation we consider the MANOVA and the GMANOVA-MANOVA models and different matrix residuals are established. The interpretation of the residuals is discussed and several properties are verified. A realistic, similar to some real studies, but artificial data will be analysed to illustrate how the residuals can be used in model validations.
Research Interests:
Matrices and statistics, with particular emphasis on canonical correlations, canonical efficiHadamard products, Matrix inequalities, Matrix partial orderings, Matrix… Read more
Achievements:
George P. H. Styan has a long and honourable career in Mathematics. He has served on the Editorial… Read more
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