A General Theoretical Framework for Learning Smallest Interpretable Models

Ordyniak, Sebastian; Paesani, Giacomo; Rychlicki, Mateusz; Szeider, Stefan

doi:10.1609/AAAI.V38I9.28937

by Sebastian Ordyniak, Giacomo Paesani, Mateusz Rychlicki, Stefan Szeider

Reference:

A General Theoretical Framework for Learning Smallest Interpretable ModelsSebastian Ordyniak, Giacomo Paesani, Mateusz Rychlicki, Stefan SzeiderAAAI'24, the Thirty-Eighth AAAI Conference on Artificial Intelligence, February 20-27, Vancouver, Canada (Jennifer Dy, Sriraam Natarajan, eds.), pages 10662–10669, 2024, AAAI Press.

Bibtex Entry:

@InProceedings{OrdyniakPaesaniRychlickiSzeider24,
  author       = {Sebastian Ordyniak and Giacomo Paesani and Mateusz
                  Rychlicki and Stefan Szeider},
  title        = {A General Theoretical Framework for Learning
                  Smallest Interpretable Models},
    booktitle = {AAAI'24, the Thirty-Eighth AAAI Conference on
                  Artificial Intelligence, February 20-27, Vancouver,
                  Canada},
  year      = {2024},
  editor    = {Jennifer Dy and Sriraam Natarajan},
  publisher = {AAAI Press},
 pages        = {10662--10669},
  publisher    = {{AAAI} Press},
  year         = {2024},
  url          = {https://doi.org/10.1609/aaai.v38i9.28937},
  doi          = {10.1609/AAAI.V38I9.28937},
    keywords  = {reveal, strides, asksat},
}