Continuous Learning in Machine Learning
Rapidly evolving machine learning requires swift adaptation. Here I'll compile a list of intriguing, up-to-date courses and complete them as time permits.
- Group Equivariant Deep Learning This course go into details about Group Equivariant Deep Learning, featuring group convolutions, equivariant graph networks, and additional resources from Amsterdam ML Lab.
- Deep Learning Foundations to Stable Diffusion This course gives a in-depth exploration of the Stable Diffusion algorithm, which is a cutting-edge technique in the field of deep learning.
- Data Science Ethics This course explore the ethical and privacy implications of big data, focusing on fairness, accountability, transparency, and responsible data management.
Academic Success Resources: Tenure, Proposals, and Job Hunting
Here I'm maintaining a centralized list of resources related to achieving tenure, securing funding proposals, and academic job hunting.
- CS Professor Handbook This book offers insights and advice on navigating academia and achieving tenure.
- You and Your Research by Richard This article discusses the steps towards achieving greatness in research.
- Student Mentoring Guide This article list resources to have clear communication and shared expectations for a successful graduate student-advisor relationship.
- Funded Proposals and Tenure Resources These are openly available funded proposals and tenure materials to learn from them.
- NSF Career Award This article shares two NSF CAREER proposals, with the first being rejected and the second being successful.
- Open Access for All This article addresses equity in academia by posting their funded proposals online for public access.
- Academic Grant Funding This article talks about department overhead, summer salary, graduate students, travel, and other expenses such as equipment and user studies.
- Academic job hunting Tips These document offers tips for academic job hunting, covering phone interviews and on-site interviews.
Technical Writing and AI Conference
This collection of resources provides strategies for enhancing technical writing skills, reviewing other papers and successfully participating in AI/ML conferences.
- Tips for Writing Effective Technical Papers This article provides a comprehensive guide to writing technical papers.
- Crafting a High-Quality ML Paper This article provides all the essentials for writing a top-notch ML paper.
- Templates for Posters This website provides visually captivating posters template and other visualization stuff.
- How to be a good reviewer ? This presentation focuses on understanding the nature of the review process in the context of AI and machine learning conferences.
- Art of Writing Effective Rebuttals This article provides a comprehensive guide on how to write effective rebuttals in AI conferences, and include tips for clarity, directness, and persuasiveness.
- AI/ML Conference Deadlines
| ML/AI Conferences | Conference Dates | Conference Deadline |
|---|---|---|
| AAAI | Feb 07-14 | Aug 15 |
| WSDM | Mar 01-03 | Aug 12 |
| SDM | Apr 27-29 | Oct 7 |
| WWW | May 01-04 | Oct 13 |
| ICLR | May 01-05 | Sep 28 |
| PAKDD | May 25-28 | Dec 7 |
| ICASSP | Jun 04-10 | Oct 26 |
| SIGIR | Jul 23-27 | Jan 31 |
| ICML | Jul 23-29 | Jan 26 |
| KDD | Aug 06-10 | Feb 02 |
| IJCAI | Aug 19-25 | Jan 18 |
| CIKM | Oct 21-25 | Jun 02 |
| ICDM | Dec 01-04 | Jul 01 |
| NeurIPS | Dec 10-16 | May 17 |