Empirical Processes
Empirical Processes is a set of lectures within the course of Advanced Statistical Methods
for the Mathematics for daTa scieNce study plan
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Bio
Anand Vidyashankar's primary research interests involve biostatistics, statistics, and biotechnology, statistical models for the Internet, statistics in finance, data confidentiality, probability, and stochastic processes. The National Science Foundation and industry partners support his research.Prerequisites
- Probability
- Statistical Inference
Aim
These set of lectures provide an introduction to the ideas and methods of Empirical Processes
Syllabus
- Motivation to Empirical Processes and High dimensional problems.
- Concentration bounds and their functional versions.
- Maximal Inequalities
- Large deviation Theory
- Uniform laws of large numbers
- Metric entropy and its applications
- Central limit Theorems
- Applications to Robust Inference and Classification problems
- Applications to Branching Processes and Markov Processes(time permitting)
References
- High-dimensional statistics - A Non-asymptotic view by Martin J. Wainwright, Cambridge University Press
- Empirical processes in M-Estimation by Sara Van der Geer, Cambridge University Press
- Mathematical Foundations of Infinite-Dimensional Statistical Models by Evarist Gine and Richard Nickl, Cambridge University Press
- Large Deviations Techniques and Applications, Second Edition, by Amir Dembo and Ofer Zeitouni, Springer Verlag.
Schedule
- 2019/06/10 9.00-12.00, Room A220 @ Povo 1
- 2019/06/11 9.00-12.00, Room A220 @ Povo 1
- 2019/06/14 9.00-12.00, Room A221 @ Povo 1
- 2019/06/17 9.00-12.00, Room A222 @ Povo 1
- 2019/06/18 9.00-12.00, Room A222 @ Povo 1
- 2019/06/20 9.00-12.00, Room A222 @ Povo 1
Details
- Poster: PDF
- Venue: Polo Scientifico e Tecnologico F. Ferrari
- Language: English
- The participation is free. Please send an email to Prof. Claudio Agostinelli.
- For further information, please contact Prof. Claudio Agostinelli