3. 강의목표
This course gives you an overview on the emerging area of "Efficient ML," i.e., building effective ML models under various resource constraints (e.g., active GPU RAM, total training FLOPs, inference latency). The main focus is on the algorithmic advances for efficient ML, while we still discuss relevant issues on the system/hardware side.
see here: https://jaeho-lee.github.io/docs/teaching/spring24/
4. 강의선수/수강필수사항
No formal requirements, but I expect you to have some elementary knowledge on machine learning and deep learning.
If you took EECE454 (or AIGS515/538 or CSED490X/Y), you should be okay.
Feel free to contact me if you are worried :)
5. 성적평가
Homework Assignments: 30%
In-class Presentations: 30%
Final Report: 30%
Participation: 10%
6. 강의교재
| 도서명 |
저자명 |
출판사 |
출판년도 |
ISBN |
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Lecture notes will be given, but I still recommend you to read the materials below.
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0000
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7. 참고문헌 및 자료
Sze, Chen, Yang, and Emer, "Efficient Processing of Deep Neural Networks," Morgan Claypool, 2020.
8. 강의진도계획
Every week, we cover different topics. For each topic, we have a brief lecture, and also a student presentation session.
Please see the course webpage: https://jaeho-lee.github.io/docs/teaching/spring24/
9. 수업운영
see the course webpage!
11. 장애학생에 대한 학습지원 사항
- 수강 관련: 문자 통역(청각), 교과목 보조(발달), 노트필기(전 유형) 등
- 시험 관련: 시험시간 연장(필요시 전 유형), 시험지 확대 복사(시각) 등
- 기타 추가 요청사항 발생 시 장애학생지원센터(279-2434)로 요청