Bibliography

Topological Order

(Iterative Deepening Depth-First Search)

  • Linear Algebra Kang/Cho
  • Matrix Calculus Scardapane -> Bright/Edelman
  • Probability Theory Piech -> Chan -> Tao -> Varadhan
  • Machine Learning Jurafsky/Martin -> Ng/Ma -> MacKay -> Murphy -> Cho
  • Deep Learning Cho -> Goodfellow -> Zhang et al -> Ermon/Grover
  • Compilers Pfenning et al. -> Myers -> Appel-> Sampson -> Muchnick
  • Chips Harris -> Hennessy -> Herlihy -> Kirk/Hwu

References

Aho, Alfred V, et al. Compilers : Principles, Techniques, and Tools. Pearson Education, 2006.

Appel, A. W., & Ginsburg, M. (2004). Modern Compiler Implementation in C. Cambridge University Press.

Bakhvalov, D. (2024). Performance Analysis and Tuning on Modern CPUs. Independently Published.

Bright, P., Edelman, A., & Johnson, S. G. (2025). Matrix Calculus (for Machine Learning and Beyond). ArXiv.org https://arxiv.org/abs/2501.14787.

Chan S. H. (2021). Introduction to Probability for Data Science. Michigan Publishing https://probability4datascience.com/.

Cho, K. (2015, November 24). Natural Language Understanding with Distributed Representation. ArXiv.org https://doi.org/10.48550/arXiv.1511.07916.

Cho, K. (2025). Machine Learning: a Lecture Note. ArXiv.org https://arxiv.org/abs/2505.03861Goodfellow.

Cooper, Keith D. “COMP 512 Lecture Notes: Advanced Compiler Construction.” Rice, 2015, https://www.clear.rice.edu/comp512/Lectures/.

Goodfellow, I., Bengio, Y., & Courville, A. (2016). Deep Learning. The MIT Press https://www.deeplearningbook.org/.

Grover, A. (2018). CS236 Deep Generative Models Course Notes. https://deepgenerativemodels.github.io/notes/.

Harris, S. L., & Harris, D. (2021). Digital Design and Computer Architecture, RISC-V Edition. Morgan Kaufmann https://pages.hmc.edu/harris/ddca/.

Hennessy, J. L., & Patterson, D. A. (2019). Computer Architecture: a Quantitative Approach. Morgan Kaufmann.

Herlihy, M., Nir Shavit, Luchangco, V., & Spear, M. (2020). The Art of Multiprocessor Programming. Newnes.

Kirk, D., & Wen-Mei Hwu. (2022). Programming Massively Parallel Processdors: a Hands-on Approach. Morgan Kaufmann Elsevier.

Krishnamurthi, Shriram. “Programming Languages: Application and Interpretation.” Plai, 2022, https://www.plai.org/.

Jurafsky, D., & Martin, J. H. (2014). Speech and Language Processing: an Introduction to Natural Language processing, Computational linguistics, and Speech Recognition. Dorling Kindersley Pvt, Ltd. https://web.stanford.edu/~jurafsky/slp3/ed3book.pdfKang.

Kang W., & Cho, K. (2025). Linear Algebra for Data Science. Kyunghyuncho.me https://kyunghyuncho.me/linear-algebra-for-data-science/Mackay.

Mackay, D. J. C. (2003). Information theory, inference, and learning algorithms. Cambridge University Press https://www.inference.org.uk/itprnn/book.pdf.

Møller , Anders, and Michael I. Schwartzbach. Static Program Analysis. 2024, https://cs.au.dk/~amoeller/spa/.

Muchnick, S. S. (2014). Advanced Compiler Design and implementation. Morgan Kaufmann

Murphy, K. P. (2022). Probabilistic machine learning : an introduction. MIT Press https://probml.github.io/pml-book/book1.html.

Murphy, K. P. (2023). Probabilistic Machine Learning: Advanced Topics. MIT Press https://probml.github.io/pml-book/book2.html.

Myers, Andrew. “CS 4120 Lecture Notes.” Cornell, 2023, https://www.cs.cornell.edu/courses/cs4120/2023sp/notes/.

Ng, A., & Ma, T. (2023). CS229 Lecture Notes https://cs229.stanford.edu/main_notes.pdf.

Piech, C. (2023). Probability for Computer Scientists. https://chrispiech.github.io/probabilityForComputerScientists/en.

Pfenning, Frank, et al. “15-411/611 Lecture Notes.” CMU, 2024, https://www.cs.cmu.edu/~janh/courses/411/24/schedule.html.

S R S Varadhan. (2001). Probability theory. Courant Institute Of Mathematical Sciences ; Providence, R.I. https://www.ams.org/books/cln/007/cln007-endmatter.pdf

Sampson, Adrian. “CS 6120 Lectures: Advanced Compilers” Cornell, 2025, https://www.cs.cornell.edu/courses/cs6120/2025sp/lesson/.

Scardapane, S. (2024). Alice’s Adventures in a Differentiable Wonderland -- Volume I, A Tour of the Land. ArXiv.org https://arxiv.org/abs/2404.17625.

Siek, Jeremy G. Essentials of Compilation. MIT Press, 1 Aug. 2023.

Tao, T. (2015). 275A Probability Theory Course Notes. https://terrytao.wordpress.com/category/teaching/275a-probability-theory/.

Zhang, A., Lipton, Z. C., Li, M., & Smola, A. J. (2023). Dive into Deep Learning. Cambridge University Press https://d2l.ai/.