Publication
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Filters: Author is Qianli Liao [Clear All Filters]
How Important Is Weight Symmetry in Backpropagation?. Thirtieth AAAI Conference on Artificial Intelligence (AAAI-16) (2016). at <https://cbmm.mit.edu/sites/default/files/publications/liao-leibo-poggio.pdf>
How Important Is Weight Symmetry in Backpropagation?. Thirtieth AAAI Conference on Artificial Intelligence (AAAI-16) (Association for the Advancement of Artificial Intelligence, 2016). liao-leibo-poggio.pdf (191.91 KB)
Learning Functions: When Is Deep Better Than Shallow. (2016). at <https://arxiv.org/pdf/1603.00988v4.pdf>
Streaming Normalization: Towards Simpler and More Biologically-plausible Normalizations for Online and Recurrent Learning. (2016). CBMM-Memo-057.pdf (1.27 MB)
Theory I: Why and When Can Deep Networks Avoid the Curse of Dimensionality?. (2016). CBMM-Memo-058v1.pdf (2.42 MB) CBMM-Memo-058v5.pdf (2.45 MB) CBMM-Memo-058-v6.pdf (2.74 MB) Proposition 4 has been deleted (2.75 MB)
How Important is Weight Symmetry in Backpropagation?. (2015). 1510.05067v3.pdf (615.32 KB)
The Invariance Hypothesis Implies Domain-Specific Regions in Visual Cortex. (2015). modularity_dataset_ver1.tar.gz (36.14 MB)
The Invariance Hypothesis Implies Domain-Specific Regions in Visual Cortex. PLOS Computational Biology 11, e1004390 (2015). journal.pcbi_.1004390.pdf (2.04 MB)
Can a biologically-plausible hierarchy effectively replace face detection, alignment, and recognition pipelines?. (2014). CBMM-Memo-003.pdf (963.66 KB)
The Invariance Hypothesis Implies Domain-Specific Regions in Visual Cortex. (2014). doi:10.1101/004473 CBMM Memo 004_new.pdf (2.25 MB)
Learning invariant representations and applications to face verification. NIPS 2013 (Advances in Neural Information Processing Systems 26, 2014). at <http://nips.cc/Conferences/2013/Program/event.php?ID=4074> Liao_Leibo_Poggio_NIPS_2013.pdf (687.06 KB)
Subtasks of Unconstrained Face Recognition. (2014). Leibo_Liao_Poggio_subtasks_VISAPP_2014.pdf (268.69 KB)