AhmadiTeshnizi, Ali, Wenzhi Gao, and Madeleine Udell. “OptiMUS: Optimization modeling using MIP solvers and large language models.” arXiv’23. [link]
May 13
GNNs for IP
Supplemental reading:
Gasse, Maxime, et al. “Exact combinatorial optimization with graph convolutional neural networks.” NeurIPS’19. [link]
Selsam, Daniel, et al. “Learning a SAT solver from single-bit supervision.” ICLR’19. [link]
May 15
Algorithm configuration
Supplemental reading:
Hutter, Frank, et al. “ParamILS: an automatic algorithm configuration framework.” Journal of Artificial Intelligence Research 36 (2009): 267-306. [link]
Theoretical guarantees
May 20
Guarantees for algorithm configuration
Supplemental reading:
Gupta, Rishi, and Tim Roughgarden. “A PAC approach to application-specific algorithm selection.” ITCS’16. [link]
Balcan, Maria-Florina. “Data-driven algorithm design.” In Beyond the worst-case analysis of algorithms, edited by Tim Roughgarden. Cambridge University Press, ‘21. [link]
May 22
Algorithms with predictions
Supplemental reading:
Purohit, Manish, et al. “Improving online algorithms via ML predictions.” NeurIPS’18. [link]
Transformers
May 29
Transformers overview
June 3
Transformers as algorithms
Supplemental reading:
Garg, Shivam, et al. “What can transformers learn in-context? a case study of simple function classes.” NeurIPS’22. [link]