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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）
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：
l What′s invariance?
l How to learn invariance?
n Traditional methods
u Tangent propagation
u Invariant kernels
n Extracting invariant features.
u Hand-crafted features
u Learned features
u Combine hand-crafted and learned features
l How to measure invariance?
n Grating test
n Natural video test
l 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.