10,640 research outputs found
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
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