References

  1. Samson Abramsky & Bob Coecke (2004): A categorical semantics of quantum protocols. In: Logic in Computer Science, 2004. Proceedings of the 19th Annual IEEE Symposium on. IEEE, pp. 415–425, doi:10.1109/LICS.2004.1319636.
  2. Dea Bankova, Bob Coecke, Martha Lewis & Dan Marsden (2016): Graded Entailment for Compositional Distributional Semantics. arXiv:1601.04908.
  3. X-D Cai, D Wu, Su Z-E, M-C Chen, Wang X-L, Li Li, N-L Liu, C-Y Lu & J-W Pan (2015): Entanglement-Based Machine Learning on a Quantum Computer. Physical Review Letters 114(11), pp. 110504, doi:10.1103/PhysRevLett.114.110504.
  4. Stephen Clark, Bob Coecke, Edward Grefenstette, Stephen Pulman & Mehrnoosh Sadrzadeh (2014): A quantum teleportation inspired algorithm produces sentence meaning from word meaning and grammatical structure. Malaysian Journal of Mathematical Sciences 8, pp. 15–25. arXiv:1305.0556.
  5. Stephen Clark, Bob Coecke & Mehrnoosh Sadrzadeh (2008): A compositional distributional model of meaning. In: Proceedings of the Second Quantum Interaction Symposium (QI-2008), pp. 133–140.
  6. Bob Coecke & Aleks Kissinger (2016): Picturing Quantum Processes. A First Course in Quantum Theory and Diagrammatic Reasoning. Cambridge University Press. To appear.
  7. Bob Coecke, Mehrnoosh Sadrzadeh & Stephen Clark (2010): Mathematical foundations for a compositional distributional model of meaning. Linguistic Analysis — A Festschrift for Jim Lambek 36. arXiv:1003.4394.
  8. Vittorio Giovannetti, Seth Lloyd & Lorenzo Maccone (2008): Quantum random access memory. Physical Review Letters 100(16), pp. 160501, doi:10.1103/PhysRevLett.100.160501.
  9. Edward Grefenstette (2013): Category-Theoretic Quantitative Compositional Distributional Models of Natural Language Semantics. Available at http://arxiv.org/abs/1311.1539.
  10. Edward Grefenstette & Mehrnoosh Sadrzadeh (2011): Experimental Support for a Categorical Compositional Distributional Model of Meaning. In: The 2014 Conference on Empirical Methods on Natural Language Processing., pp. 1394–1404.
  11. Karl Moritz Hermann & Phil Blunsom (2013): The Role of Syntax in Vector Space Models of Compositional Semantics. In: In Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics, pp. 894–904.
  12. Dimitri Kartsaklis (2015): Compositional Distributional Semantics with Compact Closed Categories and Frobenius Algebras. University of Oxford.
  13. Dimitri Kartsaklis & Mehrnoosh Sadrzadeh (2013): Prior disambiguation of word tensors for constructing Sentence vectors. In: The 2013 Conference on Empirical Methods on Natural Language Processing.. ACL, pp. 1590–1601.
  14. Dimitri Kartsaklis, Mehrnoosh Sadrzadeh & Stephen Pulman (2012): A unified sentence space for categorical distributional-compositional semantics: Theory and experiments. In: Proceedings of COLING: Posters, pp. 549–558.
  15. Joachim Lambek (2008): From word to sentence. Polimetrica, Milan.
  16. Guang Hao Low, Theodore J Yoder & Isaac L Chuang (2014): Quantum inference on Bayesian networks. Physical Review A 89(6), pp. 062315, doi:10.1103/PhysRevA.89.062315.
  17. Robin Piedeleu, Dimitri Kartsaklis, Bob Coecke & Mehrnoosh Sadrzadeh (2015): Open System Categorical Quantum Semantics in Natural Language Processing. In: Proceedings of the 6th Conference on Algebra and Coalgebra in Computer Science (CALCO), Nijmegen, Netherlands, doi:10.4230/LIPIcs.CALCO.2015.270.
  18. Tony Plate (1991): Holographic Reduced Representations: Convolution Algebra for Compositional Distributed Representations.. In: International Joint Conference on Artificial Intelligence, pp. 30–35.
  19. Tamara Polajnar, Luana Fagarasan & Stephen Clark (2013): Learning type-driven tensor-based meaning representations. arXiv:1312.5985.
  20. Patrick Rebentrost, Masoud Mohseni & Seth Lloyd (2014): Quantum support vector machine for big data classification. Physical Review Letters 113(13), pp. 130503, doi:10.1103/PhysRevLett.113.130503.
  21. Hinrich Schutze (1998): Automatic word sense discrimination. Computational Linguistics 24(1), pp. 97–123.
  22. Guoming Wang (2014): Quantum Algorithms for Curve Fitting. arXiv:1402.0660.
  23. Nathan Wiebe, Daniel Braun & Seth Lloyd (2012): Quantum algorithm for data fitting. Physical Review Letters 109(5), pp. 050505, doi:10.1103/PhysRevLett.109.050505.
  24. Nathan Wiebe, Ashish Kapoor & Krysta Svore (2015): Quantum nearest-neighbor algorithms for machine learning. Quantum Information & Computation 15(3 & 4), pp. 0318–0358.
Comments and questions to: eptcs@eptcs.org
For website issues: webmaster@eptcs.org