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发表于 2013-08-11 02:32:23 由 king

时间:2013年8月11日(周日) 下午2点半
地点海淀区学清路768创意产业园B座蕴味咖啡(公交“石板房”站,问路电话61199210)

题目Learning transformations(invariance)
主讲人:张巍,中国科学院软件所博士;
              戴玮中国科学院自动化所博士。
提纲: 

What′s invariance? 

How to learn invariance?

Traditional methods

Tangent propagation

Invariant kernels

Extracting invariant features.

Hand-crafted features

Learned features

Combine hand-crafted and learned features

How to measure invariance?

Grating test

Natural video test

Invariances in face recognition



参考文献:
Aapo Hyvarinen, Yan Karklin
【CM】Hyvarinen, A. and Hoyer, P. (2001). A two-layer sparse coding model learns simple and complex cell receptive fields and topography from natural images. Vision Research, 41(18):2413–2423.
【CM】Karklin, Y., & Lewicki, M. S. (2009). Emergence of complex cell properties by learning to generalize in natural scenes. Nature, 457(7225), 83-85.
【CM】Adelson E.H. and Bergen J.R. (1985) Spatiotemporal energy models for the perception of motion. Journal Opt. Soc. Am.
【ML】Ian J. Goodfellow, Quoc V. Le, Andrew M. Saxe, Honglak Lee, and Andrew Y. Ng. (2009) Measuring invariances in deep networks. Advances in Neural Information Processing Systems (NIPS).
补充
【ML】Q.V. Le, et, al. Building high-level features using large scale unsupervised learning. ICML, 2012. 
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