Cosmological Signature of New Parity-Violating Interactions

Does Nature yield any manifestations of parity violation other than those observed in weak interactions? A map of the cosmic microwave background (CMB) temperature and polarization will provide a new signature of P violation. We give two examples of new P violating interactions, which may have something to do with Planck-scale physics, inflation, and/or quintessence, that would give rise to such a signature. Although these effects would most likely elude detection by MAP and the Planck Surveyor, they may be detectable with a future dedicated CMB polarization experiment.Comment: 4 pages, 2 figures. Origin of new terms clarified, to be published in Physical Review Letter

Randomized hybrid linear modeling by local best-fit flats

The hybrid linear modeling problem is to identify a set of d-dimensional affine sets in a D-dimensional Euclidean space. It arises, for example, in object tracking and structure from motion. The hybrid linear model can be considered as the second simplest (behind linear) manifold model of data. In this paper we will present a very simple geometric method for hybrid linear modeling based on selecting a set of local best fit flats that minimize a global l1 error measure. The size of the local neighborhoods is determined automatically by the Jones' l2 beta numbers; it is proven under certain geometric conditions that good local neighborhoods exist and are found by our method. We also demonstrate how to use this algorithm for fast determination of the number of affine subspaces. We give extensive experimental evidence demonstrating the state of the art accuracy and speed of the algorithm on synthetic and real hybrid linear data.Comment: To appear in the proceedings of CVPR 201

Unsupervised Feature Learning by Deep Sparse Coding

In this paper, we propose a new unsupervised feature learning framework, namely Deep Sparse Coding (DeepSC), that extends sparse coding to a multi-layer architecture for visual object recognition tasks. The main innovation of the framework is that it connects the sparse-encoders from different layers by a sparse-to-dense module. The sparse-to-dense module is a composition of a local spatial pooling step and a low-dimensional embedding process, which takes advantage of the spatial smoothness information in the image. As a result, the new method is able to learn several levels of sparse representation of the image which capture features at a variety of abstraction levels and simultaneously preserve the spatial smoothness between the neighboring image patches. Combining the feature representations from multiple layers, DeepSC achieves the state-of-the-art performance on multiple object recognition tasks.Comment: 9 pages, submitted to ICL

Legislative History in Washington

This Comment begins with an examination of court usage of Washington State legislative history and illustrates the lack of consistent judicial standards for acceptance of evidence of legislative intent. It then describes a systematic process that lawyers may use to identify and obtain relevant legislative history in Washington, and at the same time, points out defects in the record-keeping system. It concludes with recommendations to the Washington State Legislature to improve the accessibility and usefulness of state legislative history. Adoption of these recommendations would not only aid the legal researcher, but also provide the legislature with a better means to convey intent and would provide the courts with reliable information to make more accurate judicial readings of legislative intent