All Publications

2016

M. Nickel, Murphy, K., Tresp, V., and Gabrilovich, E., A Review of Relational Machine Learning for Knowledge Graphs, Proceedings of the IEEE, vol. 104, no. 1, pp. 11 - 33, 2016.PDF icon 1503.00759v3.pdf (1.53 MB)
CBMM Funded
Q. Liao, Leibo, J. Z., and Poggio, T., How Important Is Weight Symmetry in Backpropagation?, in Thirtieth AAAI Conference on Artificial Intelligence (AAAI-16), Phoenix, AZ., 2016.PDF icon liao-leibo-poggio.pdf (191.91 KB)
CBMM Funded
T. Poggio, Deep Leaning: Mathematics and Neuroscience, A Sponsored Supplement to Science, vol. Brain-Inspired intelligent robotics: The intersection of robotics and neuroscience, pp. 9-12, 2016.
CBMM Funded
CBMM Memo No.
056
CBMM Funded
F. Anselmi, Rosasco, L., and Poggio, T., On invariance and selectivity in representation learning, Information and Inference: A Journal of the IMA, p. iaw009, 2016.PDF icon imaiai.iaw009.full_.pdf (267.87 KB)
CBMM Funded
CBMM Funded
W. Mlynarski and McDermott, J. H., Learning mid-level codes for natural sounds, Computational and Systems Neuroscience (Cosyne) 2016. Salt Lake City, UT, 2016.PDF icon Wiktor_COSYNE_2015_hierarchy_final.pdf (2.52 MB)
CBMM Funded
F. Bach and Poggio, T., Introduction Special issue: Deep learning, Information and Inference, vol. 5, pp. 103-104, 2016.
CBMM Funded
Q. Liao, Leibo, J. Z., and Poggio, T., How Important Is Weight Symmetry in Backpropagation?, in Thirtieth AAAI Conference on Artificial Intelligence (AAAI-16), Phoenix, AZ., 2016.
CBMM Funded
M. Nickel, Rosasco, L., and Poggio, T., Holographic Embeddings of Knowledge Graphs, in Thirtieth AAAI Conference on Artificial Intelligence (AAAI-16), Phoenix, Arizona, USA, 2016.PDF icon 1510.04935v2.pdf (360.65 KB)
CBMM Funded
O. Lewis and Poggio, T., Object and Scene Perception, in From Neuron to Cognition via Computational Neuroscience, Cambridge, MA, USA: The MIT Press, 2016.
CBMM Funded