---
# System prepended metadata

title: Agenda for 16.04.2021 supervision meeting
tags: [Supervision]

---

###### tags: `Supervision`

# Agenda for 16.04.2021 supervision meeting

* What we discuss mainly: Survey on Multi-Fairness. 
* Study the Multi-Objective Fairness papers and try to organize and write a survey.
* Also the direction of "AdaFair, FAHT, Adwin, Gradient Boosting" is to be maintained.
* Arjun wants to know my idea about the Min-Max ICML 2020 paper and other MOA in Fairness.
* The new paper that Eirini introduced will be discussed : "A generic algorithm for reducing bias in parametric estimation".
* Grant Agreement and our next movement for the grant
## Zotero Library:
I created a library in zotero of almost All new MO-Fairness papers.
* "Multi-Objective_Fairness_Learning"

    This main folder is for survey papers. here is the link for the Library: https://www.zotero.org/groups/2844476/phd_literature/collections/IHK5CB8Y
    * There is a sub-folder: "MOFariness Applications" including MO-Fariness papers in the Industry or Economics
    * Another sub-category is the "Multi-Objective Machine Learning" that includes newest highly impact publications in top proceedings about MOAs in different Machine Learning areas. 
        * Reinforcement Learning
        * Multi-Task Learning 
        * Multi-Objective Gradient Descent

## Reference Books
* Understanding Machine Learning: From Theory to Algorithms
    * Shai Shalev-Shwartz
* An Introduction to Statistical Learning
    * Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani
    * https://www.statlearning.com/
* Deep Learning
    * Aaron Courville, Ian Goodfellow, and Yoshua Bengio
* Fairness and machine learning
    * https://fairmlbook.org/
    * Solon Barocas, Moritz Hardt, Arvind Narayanan  
* Convex Optimization
    * Stephen Boyd
* Mathematics for Machine Learning
    * Marc Peter Deisenroth 
*  Probably a book for Online Learning
* A reference book for Multi-Objective Optimization

## Courses:
* Now I am catching up with Andrew NG's online ML course
* I might need to attend an online learning course. If you know a good one