# Coming Events

## Seminar by S Guin

Date/Time:
Thursday, February 22, 2018 - 15:00 to 16:00
Venue:
Seminar Room, School of Mathematical Sciences
Speaker:
Satyajit Guin
Affiliation:
IISER Mohali
Title:
TBA

TBA

## Math Talk by S Ray

Date/Time:
Tuesday, March 6, 2018 - 17:30 to 18:30
Speaker:
Swagato K Ray
Affiliation:
ISI Kolkata
Title:
TBA

TBA

## Seminar by S. Ray

Date/Time:
Wednesday, March 7, 2018 - 14:30 to 15:30
Venue:
Seminar Room, School of Mathematical Sciences
Speaker:
Swagato K Ray
Affiliation:
ISI Kolkata
Title:
TBA

TBA

## Seminar

Date/Time:
Monday, March 12, 2018 - 11:40 to 12:40
Venue:
SMS Seminar Hall
Speaker:
Deepika
Affiliation:
IIT Kanpur
Title:
Approximation Property and Its Variants in Weighted Spaces of Holomorphic Functions on Banach Spaces
Abstract:- Let $E$ be a complex Banach space and $U$ be an open subset of $E$. Corresponding to a weight $w$(a strictly positive continuous function) defined on U, the weighted space of holomorphic functions is defined as $$\mathcal{H}_w(U) = \{ f\in \mathcal{H}(U) : \|f\|_w = \sup_{x\in U}w(x)\|f(x)\|\leq 1\}.$$ The space $(\mathcal{H}_w(U),~ \|\cdot\|_w)$ is a dual Banach space and its predual $\mathcal{G}_w(U)$ is given by \begin{align*} \mathcal{G}_w(U)=\{\phi \in \mathcal{H}_w(U)^\prime: \phi |B_w ~\textrm{is}~ \tau_0 -\textrm{continuous}\} \end{align*} where $B_w$ denotes the closed unit ball of the weighted space $(\mathcal{H}_w(U),~ \|\cdot\|_w)$. In this talk, we consider the approximation property and its variants for $\mathcal{H}_w(U)$ and its predual $\mathcal{G}_w(U)$. After introducing a locally convex topology $\tau_\mathcal{M}$ on these spaces, we show that the weighted space equipped with the topology $\tau_\mathcal{M}$ becomes topologically isomorphic to the class of linear operators endowed with the topology of uniform convergence on compact sets. This leads us to characterize the approximation property for a complex Banach space $E$ in terms of the approximation property for these spaces. Further, we characterize the bounded approximation property for weighted Fr\'{e}chet and (LB)-spaces using the techniques of $\mathcal{S}$-absolute decompositions

## seminar

Date/Time:
Monday, March 19, 2018 - 15:35 to 16:30
Venue:
SMS seminar room
Speaker:
Anirvan Chakraborty
Affiliation:
Ecole Polytechnique Federale de Lausanne, Switzerland
Title:
Introduction to Functional Data Analysis

Functional Data Analysis is one of the frontline areas of research in statistics. The field has grown considerably mainly due to the plethora of data types that cannot be handled and analyzed by using conventional multivariate statistical techniques. Such data are very common in areas of meteorology, chemometrics, biomedical sciences, linguistics, finance etc .The lecture series will primarily aim at introducing the field of functional data analysis. Since functional data analysis is broadly defined as the statistical analysis of data, which are in the form of curves or functions, we will start with probability distributions and random elements in infinite dimensional Hilbert spaces, concepts of mean and covariance kernel/operator, the associated Karhunen-Loeve expansion and some standard limit theorems in Hilbert spaces. We will then discuss some selected statistical inference problems involving functional data like inference for mean and covariance operators, functional principal component analysis, functional linear models, classification problem with functional data, robust inference techniques for functional data etc. We will recall some results from functional analysis as and when required during the lectures.

## seminar

Date/Time:
Tuesday, March 20, 2018 - 15:35 to 16:30
Venue:
SMS seminar room
Speaker:
Anirvan Chakraborty
Affiliation:
Ecole Polytechnique Federale de Lausanne, Switzerland
Title:
Introduction to Functional Data Analysis

Functional Data Analysis is one of the frontline areas of research in statistics. The field has grown considerably mainly due to the plethora of data types that cannot be handled and analyzed by using conventional multivariate statistical techniques. Such data are very common in areas of meteorology, chemometrics, biomedical sciences, linguistics, finance etc .The lecture series will primarily aim at introducing the field of functional data analysis. Since functional data analysis is broadly defined as the statistical analysis of data, which are in the form of curves or functions, we will start with probability distributions and random elements in infinite dimensional Hilbert spaces, concepts of mean and covariance kernel/operator,  the associated Karhunen-Loeve expansion and some standard limit theorems in Hilbert spaces. We will then discuss some selected statistical inference problems involving functional data like inference for mean and covariance operators, functional principal component analysis, functional linear models, classification problem with functional data, robust inference techniques for functional data etc. We will recall some results from functional analysis as and when required during the lectures.

## seminar

Date/Time:
Wednesday, March 21, 2018 - 14:35 to 15:30
Venue:
SMS seminar room
Speaker:
Anirvan Chakraborty
Affiliation:
Ecole Polytechnique Federale de Lausanne, Switzerland
Title:
Introduction to Functional Data Analysis

Functional Data Analysis is one of the frontline areas of research in statistics. The field has grown considerably mainly due to the plethora of data types that cannot be handled and analyzed by using conventional multivariate statistical techniques. Such data are very common in areas of meteorology, chemometrics, biomedical sciences, linguistics, finance etc .The lecture series will primarily aim at introducing the field of functional data analysis. Since functional data analysis is broadly defined as the statistical analysis of data, which are in the form of curves or functions, we will start with probability distributions and random elements in infinite dimensional Hilbert spaces, concepts of mean and covariance kernel/operator, the associated Karhunen-Loeve expansion and some standard limit theorems in Hilbert spaces. We will then discuss some selected statistical inference problems involving functional data like inference for mean and covariance operators, functional principal component analysis, functional linear models, classification problem with functional data, robust inference techniques for functional data etc. We will recall some results from functional analysis as and when required during the lectures.

## seminar

Date/Time:
Thursday, March 22, 2018 - 15:35 to 16:30
Venue:
SMS seminar room
Speaker:
Anirvan Chakraborty
Affiliation:
Ecole Polytechnique Federale de Lausanne, Switzerland
Title:
Introduction to Functional Data Analysis

Functional Data Analysis is one of the frontline areas of research in statistics. The field has grown considerably mainly due to the plethora of data types that cannot be handled and analyzed by using conventional multivariate statistical techniques. Such data are very common in areas of meteorology, chemometrics, biomedical sciences, linguistics, finance etc .The lecture series will primarily aim at introducing the field of functional data analysis. Since functional data analysis is broadly defined as the statistical analysis of data, which are in the form of curves or functions, we will start with probability distributions and random elements in infinite dimensional Hilbert spaces, concepts of mean and covariance kernel/operator, the associated Karhunen-Loeve expansion and some standard limit theorems in Hilbert spaces. We will then discuss some selected statistical inference problems involving functional data like inference for mean and covariance operators, functional principal component analysis, functional linear models, classification problem with functional data, robust inference techniques for functional data etc. We will recall some results from functional analysis as and when required during the lectures.