Bayesian ASYMPTOTIC theory

Must-Know Concentration Inequality

• Inequalities and Asymptotic Estimates  [Link]

• Concentration Inequalities [Link]

• Concentration Inequalities [Link1] [Link2]

• Concentration Inequality [Link]

• Introduction to Concentration Inequalities  [Link]

• Lecture Series on Concentration Inequality [Link]

• Lecture Slide [Link1] [Link2]

• Stanford Lecture [Link]

• An introduction to matrix concentration inequalities [Link]

• Materials [Link]

Influential & Must-Read Papers for Bayesian Asymptotic Theory

• The exponential convergence of posterior probabilities with implications for Bayes estimators of density functions by Barron in 1988 [Link]

• Papers listed in the website [Link]

Self-learning material for the basics of posterior consistency/contraction/asymptotic

• Prof. Surya Tokdar: Note on Bayesian Asymptotic [Link]

• Profs. Debdeep Pati and Anirban Bhattacharya: Slide on Bayesian Asymptotic [Link]

• Profs. S. Ghosal, J. K. Ghosh and R. V. Ramamoorthi: Consistency issues in Bayesian Nonparametrics [Link]

• Youtube Lecture by Prof. Debdeep Pati: [Link1] [Link2]

• Bayes Factor Consistency : [Link]

• Prof. Bas Kleijn: Bayesian Statistics [Link]

• STATISTICAL ASYMPTOTICS  [Link]

• Prof. Anirban Bhattacharya Statistical guarantees for variational Bayes [Link]

• Prof. Peter Hoff: Minimax Estimation [Link]

• Prof. S. Ghosal: A REVIEW OF CONSISTENCY AND CONVERGENCE OF POSTERIOR DISTRIBUTION [Link]

• Prof. Debdeep's Lecture Slide [Link]

• Prof. Van der Vaart Lectures on Nonparametric Bayesian Statistics  [Link]

Basic of Bayesian Nonparametrics

• Prof. Peter Orbanz: Lecture Notes on Bayesian Nonparametrics  [Link]

• Prof. Larry Wasserman: Bayesian Inference  [Link]

• Bayesian Short Course [Link1] [Link2] [Link3]

Minmax Theory [How well does the best learning algorithm do in the worst case scenario? Minimax Rate = “Best Possible Guarantee” ]

• Prof. Larry Wasserman: Minimax Theory  [Link] [Video]

• Prof. Ryan Tibshirani : Minimax Theory for Nonparametric Regression [Link] 

• Machine Learning Theory [Link] 

• Prof. Lester Mackey [Link]

• Prof. Siva Balakrishnan  [Link]

• Prof. Anirban Bhattacharya & Debdeep Pati  [Link]

Papers to read

• Regression Shrinkage and Selection Via the Lasso, Robert Tibshirani, [Link]