All Publications

2016

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
D. Rockmore, “The Trolley Problem [Edge.com]”. Edge.com, 2016.PDF icon The Trolley Problem.pdf (343.3 KB)
CBMM Memo No.
059
D. Harari, Gao, T., Kanwisher, N., Tenenbaum, J. B., and Ullman, S., “Measuring and modeling the perception of natural and unconstrained gaze in humans and machines”. 2016.PDF icon CBMM-Memo-059.pdf (1.71 MB)
CBMM Funded
CBMM Memo No.
058
T. Poggio, Mhaskar, H., Rosasco, L., Miranda, B., and Liao, Q., “Theory I: Why and When Can Deep Networks Avoid the Curse of Dimensionality?”. 2016.PDF icon CBMM-Memo-058v1.pdf (2.42 MB)PDF icon CBMM-Memo-058v5.pdf (2.45 MB)PDF icon CBMM-Memo-058-v6.pdf (2.74 MB)PDF icon Proposition 4 has been deleted (2.75 MB)
CBMM Funded
G. Ben-Yosef, Yachin, A., and Ullman, S., “Recognizing and Interpreting Social Interactions in Local Image Regions”, The 24th Annual Workshop on Object Perception, Attention, and Memory (OPAM), Boston, MA. 2016.
CBMM Funded
B. Katz and Barbu, A., “A look back at the June 2016 BMM Workshop in Sestri Levante, Italy”. 2016.PDF icon Sestri Levante Review (359.33 KB)
CBMM Funded
A. Rosenfeld and Ullman, S., “Visual Concept Recognition and Localization via Iterative Introspection. ”, in Asian Conference on Computer Vision, 2016.PDF icon Focusing on parts of interest  (910.14 KB)
CBMM Related
M. Tegmark, “Improved Measures of Integrated Information”, PLOS Computational Biology, 2016.PDF icon 1601.02626.pdf (3.49 MB)
CBMM Related
CBMM Memo No.
057
Q. Liao, Kawaguchi, K., and Poggio, T., “Streaming Normalization: Towards Simpler and More Biologically-plausible Normalizations for Online and Recurrent Learning”. 2016.PDF icon CBMM-Memo-057.pdf (1.27 MB)
CBMM Funded
CBMM Memo No.
056
I. Dasgupta, Schulz, E., and Gershman, S. J., “Where do hypotheses come from?”. 2016.PDF icon CBMM-Memo-056-v2.pdf (733.35 KB)
CBMM Funded
CBMM Memo No.
053
G. Dehaene-Lambertz and Spelke, E. S., “The infancy of the human brain”. 2016.PDF icon CBMM-Memo-053.pdf (1.51 MB)
CBMM Funded
A. Owens, Isola, P., McDermott, J. H., Freeman, W. T., and Torralba, A., “Lecture Notes in Computer ScienceComputer Vision – ECCV 2016Ambient Sound Provides Supervision for Visual Learning”, 14th European Conference on Computer Vision. Cham, pp. 801 - 816, 2016.
CBMM Funded
H. Tang, Singer, J., Ison, M. J., Pivazyan, G., Romaine, M., Frias, R., Meller, E., Boulin, A., Carroll, J., Perron, V., Dowcett, S., Arellano, M., and Kreiman, G., “Predicting episodic memory formation for movie events”, Scientific Reports, no. 1, 2016.
CBMM Memo No.
055
Y. Berzak, Huang, Y., Barbu, A., Korhonen, A., and Katz, B., “Anchoring and Agreement in Syntactic Annotations”. 2016.PDF icon CBMM-Memo-055.pdf (768.54 KB)
CBMM Related
CBMM Memo No.
051
Y. Berzak, Barbu, A., Harari, D., Katz, B., and Ullman, S., “Do You See What I Mean? Visual Resolution of Linguistic Ambiguities”. 2016.PDF icon memo-51.pdf (2.74 MB)
CBMM Funded
Z. Chen, Linderman, S. W., and Wilson, M. A., “Bayesian nonparametric methods for discovering latent structures of rat hippocampal ensemble spikes”, in IEEE Workshop on Machine Learning for Signal Processing, Salerno, Italy, 2016.PDF icon MLSP16 (1).pdf (1.04 MB)
CBMM Funded
T. Poggio and Anselmi, F., Visual Cortex and Deep Networks: Learning Invariant Representations. Cambridge, MA, USA: The MIT Press, 2016, p. 136.
CBMM Funded
J. Traer and McDermott, J. H., “Statistics of natural reverberation enable perceptual separation of sound and space”, Proceedings of the National Academy of Sciences, vol. 113, no. 48, pp. E7856 - E7865, 2016.
CBMM Funded
F. Xia, Wang, P., Chen, L. -chieh, and Yuille, A., “Zoom better to see clearer: Human and object parsing with hierarchical auto-zoom net”, in ECCV, Amsterdam, The Netherlands, 2016.PDF icon auto-zoom_net.pdf (5.77 MB)
CBMM Funded
C. E. Robertson, Hermann, K., Mynick, A., Kravitz, D. J., and Kanwisher, N., “Neural Representations Integrate the Current Field of View with the Remembered 360° Panorama”, Current Biology, 2016.
CBMM Funded
CBMM Memo No.
054
H. Mhaskar and Poggio, T., “Deep vs. shallow networks : An approximation theory perspective”. 2016.PDF icon Original submission, visit the link above for the updated version (960.27 KB)
CBMM Funded
Y. Berzak, Kenney, J., Spadine, C., Wang, J. Xian, Lam, L., Mori, K. Sophie, Garza, S., and Katz, B., “Treebank of Learner English (TLE)”. 2016.PDF icon acl2016.pdf (163.86 KB)
CBMM Funded
Z. Chen, Grosmark, A. D., Penagos, H., and Wilson, M. A., “Uncovering representations of sleep-associated hippocampal ensemble spike activity”, Scientific Reports, vol. 6, 2016.
CBMM Funded
CBMM Memo No.
050
Y. Berzak, Reichart, R., and Katz, B., “Contrastive Analysis with Predictive Power: Typology Driven Estimation of Grammatical Error Distributions in ESL”. 2016.PDF icon memo-50.pdf (493.74 KB)
CBMM Funded
CBMM Memo No.
052
Y. Berzak, Kenney, J., Spadine, C., Wang, J. Xian, Lam, L., Mori, K. Sophie, Garza, S., and Katz, B., “Universal Dependencies for Learner English”. 2016.PDF icon memo-52_rev1.pdf (472.67 KB)
CBMM Funded

Pages