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Course Detail

Course Name SVD and ADMM revisited
Course Code 24AIM341
Program B.Tech. in Artificial Intelligence (AI) and Data Science (Medical Engineering)
Semester VI
Credits 3
Campus Coimbatore

Summary

CO: The student should be able to apply SVD and ADMM for LP, QP and LASSO.

SVD and Latent Semantic Analysis-SVD and Image Compression-DCT-SVD based Steganography -Pseudo Inverse, Multivariate regression, Classification-SVD and large Language model fine tuning-Constraint optimization and Lagrangian Multiplier- ADMM Philosophy, ADMM for LP, QP, LASSO

References

  1. https://www.cs.cmu.edu/~venkatg/teaching/CStheory-infoage/book-chapter-4.pdf
  2. James Bisgard (author) Analysis and Linear Algebra: The Singular Value Decomposition and Applications
  3. Gilbert Strang , https://math.mit.edu/~gs/linearalgebra/ila5/linearalgebra5_7-1.pdf
  4. https://web.stanford.edu/class/cs276/handouts/lecture13-lsi-handout-1-per.pdf
  5. DCT-SVD based Steganography https://eudl.eu/pdf/10.4108/eai.28-9-2020.166365
  6. https://medium.com/@Shrishml/lora-low-rank-adaptation-from-the-first-principle-7e1adec71541
  7. https://web.stanford.edu/~boyd/papers/admm/

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