Dakotah Lambert

Interests

I received a PhD from Stony Brook University for my work in Mathematical Linguistics. Through algebraic and logical analysis, I aim to understand the structures that arise in communication between and among humans and computers, including natural languages (human–human communication), programming languages (human–computer communication), and signaling protocols (computer–computer communication). Parameterization and decomposition of these systems arise out of their structure and inform mechanisms for recognition and learning. I have also applied these techniques to pattern-learning by neural networks, which provides insight and explainability for such models.

Projects

Over the years I have been building an interactive theorem-prover for subregular logics. Implemented in Haskell as both a library and supporting command-line tools, the Language Toolkit (LTK) enables somewhat easy translation from constraints to automata (and, in some cases, the reverse translation). For any regular language, the LTK can also determine which of several subregular classes that language is in, including those defined by logical properties or those induced by user-specified pseudovarieties of semigroups or monoids.

Publications

• Philip Kaelbling, Dakotah Lambert, and Jeffrey Heinz. 2023. Robust identification in the limit from incomplete positive data. In Henning Fernau and Klaus Jansen, editors, Fundamentals of Computation Theory: 24th International Symposium, FCT 2023, volume 14292 of Lecture Notes in Computer Science, pages 276–290. Springer, Cham.
• Rémi Eyraud, Dakotah Lambert, Badr Tahri Joutei, Aidar Gaffarov, Mathias Cabanne, Jeffrey Heinz, and Chihiro Shibata. 2023. TAYSIR competition: Transformer+RNN: Algorithms to yield simple and interpretable representations. In Proceedings of the 16th edition of the International Conference on Grammatical Inference, volume 217 of Proceedings of Machine Learning Research, pages 275–290.
• Dakotah Lambert and Jeffrey Heinz. 2023. An algebraic characterization of total input strictly local functions. In Proceedings of the Society for Computation in Linguistics, volume 6, pages 25–34, Amherst, Massachusetts.
• Dakotah Lambert. 2023. Relativized adjacency. Journal of Logic, Language and Information, 32(4):707–731.
• Dakotah Lambert. 2022. Unifying Classification Schemes for Languages and Processes with Attention to Locality and Relativizations Thereof. Ph.D. thesis, Stony Brook University.
• Dakotah Lambert. 2021. Grammar interpretations and learning TSL online. In Proceedings of the Fifteenth International Conference on Grammatical Inference, volume 153 of Proceedings of Machine Learning Research, pages 81–91.
• Dakotah Lambert, Jonathan Rawski, and Jeffrey Heinz. 2021. Typology emerges from simplicity in representations and learning. Journal of Language Modelling, 9(1):151–194. Institute of Computer Science, Polish Academy of Sciences.
• Dakotah Lambert and James Rogers. 2020. Tier-based strictly local stringsets: Perspectives from model and automata theory. In Proceedings of the Society for Computation in Linguistics, volume 3, pages 330–337, New Orleans, Louisiana.
• James Rogers and Dakotah Lambert. 2019. Extracting Subregular constraints from Regular stringsets. Journal of Language Modelling, 7(2):143–176. Institute of Computer Science, Polish Academy of Sciences.
• James Rogers and Dakotah Lambert. 2019. Some classes of sets of structures definable without quantifiers. In Proceedings of the 16th Meeting on the Mathematics of Language, pages 63–77, Toronto, Canada. Association for Computational Linguistics.
• Dakotah Lambert and James Rogers. 2019. A logical and computational methodology for exploring systems of phonotactic constraints. In Proceedings of the Society for Computation in Linguistics, volume 2, pages 247–256, New York City, New York.
• James Rogers and Dakotah Lambert. 2017. Extracting forbidden factors from Regular stringsets. In Proceedings of the 15th Meeting on the Mathematics of Language, pages 36–46, London, UK. Association for Computational Linguistics.
• Dakotah Lambert, Margaret Fero, Andrew Dai, and James Rogers. 2014. A workbench for logically definable stringsets. In Proceedings of the 2014 Midstates Conference for Undegraduate Research in Computer Science and Mathematics, pages 47–52, Wooster, OH.
• James Rogers, Jeffrey Heinz, Margaret Fero, Jeremy Hurst, Dakotah Lambert, and Sean Wibel. 2012. Cognitive and sub-regular complexity. In Glyn Morrill and Mark-Jan Nederhof, editors, Formal Grammar 2012, volume 8036 of Lecture Notes in Computer Science, pages 90–108. Springer Verlag.