Browsing by Author "Calderbank, R"
Now showing items 1-4 of 4
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Communications inspired linear discriminant analysis
(Proceedings of the 29th International Conference on Machine Learning, ICML 2012, 2012-10-10)We study the problem of supervised linear dimensionality reduction, taking an information-theoretic viewpoint. The linear projection matrix is designed by maximizing the mutual information between the projected signal and ... -
Communications-inspired projection design with application to compressive sensing
(SIAM Journal on Imaging Sciences, 2012-12-01)We consider the recovery of an underlying signal x ∈ ℂm based on projection measurements of the form y = Mx+w, where y ∈ ℂℓ and w is measurement noise; we are interested in the case ℓ ≪ m. It is assumed that the signal model ... -
DCFNet: Deep Neural Network with Decomposed Convolutional Filters
(35th International Conference on Machine Learning, ICML 2018, 2018-01-01)©35th International Conference on Machine Learning, ICML 2018.All Rights Reserved. Filters in a Convolutional Neural Network (CNN) contain model parameters learned from enormous amounts of data. In this paper, we suggest ... -
RotDCF: Decomposition of Convolutional Filters for Rotation-Equivariant Deep Networks.
(CoRR, 2018)Explicit encoding of group actions in deep features makes it possible for convolutional neural networks (CNNs) to handle global deformations of images, which is critical to success in many vision tasks. This paper proposes ...
