Cameron Freer

Postdoctoral Associate, MIT Brain and Cognitive Sciences
Lyric Labs Visiting Fellow, Analog Devices
Research Scientist, Gamelan Labs
freer@math.removethis.mit.andthis.edu

32-G480
Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology

32 Vassar Street
Cambridge, MA 02139

Office Phone: (617) 253-2897

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Research

My research interests are in the computability and complexity theory of probabilistic inference, computable probability theory, the model theory of graphs and graph limits, and the physics of causality and computation.

 

Curriculum Vitae

 

Publications

Algorithmic aspects of Lipschitz functions, with Bjørn Kjos-Hanssen, André Nies, and Frank Stephan, Computability 3, 1–17, 2014. arXiv:1402.2429.

Towards common-sense reasoning via conditional simulation: legacies of Turing in Artificial Intelligence, with Daniel Roy and Joshua Tenenbaum, in Turing's Legacy: Developments from Turing's Ideas in Logic, ed. Rod Downey, ASL Lecture Notes in Logic, Cambridge Univ. Press, 2014. arXiv:1212.4799.

Randomness extraction and asymptotic Hamming distance, with Bjørn Kjos-Hanssen, Selected Papers of the Ninth International Conference on Computability and Complexity in Analysis (CCA 2012), Logical Methods in Computer Science, 2013. arXiv:1008.0821.

Causal entropic forces, with Alexander Wissner-Gross, Physical Review Letters 110, 168702, 2013. Supplemental Material.

A notion of a computational step for Partial Combinatory Algebras, with Nate Ackerman, in Proceedings of the 10th Annual Conference on Theory and Applications of Models of Computation (TAMC 2013), LNCS Vol. 7876, 133–143, 2013.

Computable de Finetti measures, with Daniel Roy, Annals of Pure and Applied Logic 163, no. 5, 530–546, 2012. arXiv:0912.1072.

Noncomputable conditional distributions, with Nate Ackerman and Daniel Roy, in Proceedings of the 26th Annual IEEE Symposium on Logic in Computer Sci. (LICS 2011), 107–116, 2011.

Relativistic statistical arbitrage, with Alexander Wissner-Gross, Physical Review E 82, 056104, 2010.

Posterior distributions are computable from predictive distributions, with Daniel Roy, in Proceedings of the 13th International Conference on Artificial Intelligence and Statistics (AISTATS 2010), Journal of Machine Learning Research (JMLR) Workshop and Conference Proceedings 9, 2010.

Computable exchangeable sequences have computable de Finetti measures, with Daniel Roy, in Mathematical Theory and Computational Practice, Proceedings of Computability in Europe (CiE 2009), LNCS Vol. 5635, 218–231, 2009.

 

Preprints

Invariant measures concentrated on countable structures, with Nate Ackerman and Rehana Patel. arXiv:1206.4011.

Invariant measures via inverse limits of finite structures, with Nate Ackerman, Jaroslav Nešetřil, and Rehana Patel. arXiv:1310.8147.

On the computability of conditional probability, with Nate Ackerman and Daniel Roy. arXiv:1005.3014.

 

PhD Thesis

Models with High Scott Rank, PhD thesis, Harvard University, 2008.

 

Patents

System and method for relativistic statistical securities trading, with Alexander Wissner-Gross, U.S. Patent 8,635,133 (2014).

 

PGP Public Key

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