Professional Research Development Course in Machine Learning Theory

We can contribute to the development of fundamental topics in Machine Learning and publish our research in top peer-reviewed conferences! Work with an experienced researcher in the field.

This course is aimed at early career researchers who are interested in cutting edge academic research in theoretical machine learning - including but not limited to reinforcement learning, deep learning and optimization. The aim of the course is to jointly work and solve a problem in the aforementioned fields and publish in a top conferences (Example: ICML, NeurIPS etc.). If we do not publish in the agreed upon venue, YOU WILL HAVE YOUR MONEY BACK.  (refer to the refund policy below) 

I have extensive experience in publishing top tier research in these venues (NeurIPS, ICML and COLT) and several math journals (like Annals of Applied Probability, SIAM Journal of Optimization and Probability Theory and Related fields ). 

My Google Scholar page:
https://scholar.google.com/citations?user=0g80b7sAAAAJ&hl=en


Description of the Course:

1. Enrollment limited to 4 per course, fully online.

2. This cycle we will be working on theoretical aspects of Reinforcement Learning.

3. I will present the problem, some background, and potential avenues for solution (~10 hours and more if necessary)

4. Enrolled researchers spend time presenting and discussing techniques which can be used to solve the problem at hand along with related works.

5. Transcripts of the discussions will be maintained for full transparency of contributions. Video recording of presentations is optional. 

6. Spend ~20 hours each writing the manuscript collectively.

7. Contact details for the course is available in the document available to download once the payment is made. 

8. This will be a purely mathematical course and the resultant research will be theoretical in nature, but some simulations maybe employed to illustrate the theory.

Note: This is a research level course and some familiarity with the topics is assumed. That said, I will introduce some of the specific technical topics which maybe used. You will agree to maintain academic integrity expected out of a leading researcher. I reserve the right to un-register you from the course for unethical behavior and refund you based on the refund policy below.

Refund policy:
1. If you complete the course and we do not end up publishing the manuscript in one of the agreed upon conferences after 2 submissions, you will get a complete refund.

2. If you choose to quit the course before beginning, you will get a complete refund.

3. If you choose to quit in the middle of the course, then
 a. 80% refund if we are in the middle of step 3 ( see course description)
 b. 60% refund if we are in the middle of step 4 (course description)
 c. 40% refund afterwards. 

4. If you choose to drop out of the course, you agree to not reveal or publish the contents of the project without explicit consent from me. You agree to withdraw from the project and the resulting publications.