SANDMAN

Lab Meeting Schedule:

Theme: Novel Architectures for Learning Distributed Semantic Representations

Internal Codename: Semantic Architectures 'N Distributional Memory And Neurons? (SANDMAN)

Date	Topic/Readings
Feb 7	BEAGLE (Mike) Jones, M. N., & Mewhort, D. J. K. (2007). Representing word meaning and order information in a composite holographic lexicon. Psychological Review, 114, 1-37.
Feb 14	Sparse Binary Memory Systems (Mike) Kanerva, P. (2009). Hyperdimensional computing: An introduction to computing in distributed representation with high-dimensional random vectors. Cognitive Computation, 1(2), 139-159. Recchia, G. L., Sahlgren, M., Kanerva, P., & Jones, M. N. (2015). Encoding sequential information in vector space models of semantics: Comparing holographic reduced representation and random permutation.Computational Intelligence & Neuroscience. An Introduction to Random Indexing (Magnus Sahlgren) https://www.slideshare.net/dileepajayakody/w-40109236
Feb 21	Holographic Neural Networks (Mike) Jones, M. N. (2007). Holographic Neural Networks. Poster Presented at Psychonomic Society Annual Meeting Plate, T. A. (2003) Convolution-based memory models.Encyclopedia of Cognitive Science. Plate, T. A. (1995). Holographic Reduced Representations. IEEE Transactions on Neural Networks. Plate, T. (1992). Holographic Recurrent Networks. NIPS-5. Kelly, M. A., Blostein, D., & Mewhort, D. J. K. (2013). Encoding structure in holographic reduced representations. CJEP.
Feb 28	Kiran Kumar: Exploring NYT article data to understand individual and stylistic changes over years Chen, D., & Manning, C. (2014). A fast and accurate dependency parser using neural networks. In Proceedings of the 2014 conference on empirical methods in natural language processing (EMNLP) (pp. 740-750). Chen, W. T., & Palmer, M. (2017). Unsupervised AMR-dependency parse alignment. In Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers (Vol. 1, pp. 558-567). Chicago
Mar 7	Brand new hybrid structure + processing account: Rotaru, A. S., Vigliocco, G., & Frank, S. L. (2018, February 9). Modelling the structure and dynamics of semantic processing. Retrieved from psyarxiv.com/d8auy
Mar 14	Spring Break
Mar 21	Brand new hybrid structure + processing account: Rotaru, A. S., Vigliocco, G., & Frank, S. L. (2018, February 9). Modelling the structure and dynamics of semantic processing. Retrieved from psyarxiv.com/d8auy
Mar 28	Mike @ CMU
Apr 4	Mike in DC
Apr 11	Quantum Semantic Models (Erik) Bruza, P. D., & Cole, R. J. (2006). Quantum logic of semantic space: An exploratory investigation of context effects in practical reasoning. arXiv preprint quant-ph/0612178. Bruza, P., Kitto, K., Nelson, D., & McEvoy, C. (2009). Is there something quantum-like about the human mental lexicon?. Journal of Mathematical Psychology, 53(5), 362-377.
Apr 18	Elastic Weight Consolidation (Keiland) Kirkpatrick, J., Pascanu, R., Rabinowitz, N., Veness, J., Desjardins, G., Rusu, A. A., ... & Hassabis, D. (2017). Overcoming catastrophic forgetting in neural networks. Proceedings of the National Academy of Sciences, 114(13), 3521-3526. French, R. M. (1999). Catastrophic forgetting in connectionist networks. Trends in cognitive sciences, 3(4), 128-135. Hasselmo, M. E. (2017). Avoiding catastrophic forgetting. Trends in cognitive sciences, 21(6), 407-408. Chicago
Apr 25	Spiking Neural Networks (Prudhvi) Stewart, T. C., Bekolay, T., & Eliasmith, C. (2011). Neural representations of compositional structures: Representing and manipulating vector spaces with spiking neurons. Connection Science, 23(2), 145-153. Vreeken, J. (2003). Spiking neural networks, an introduction.
May 2	Reservoir Computing (Jack)