The IBMAP approach for Markov networks structure learning

In this work we consider the problem of learning the structure of Markov networks from data. We present an approach for tackling this problem called IBMAP, together with an efficient instantiation of the approach: the IBMAP-HC algorithm, designed for avoiding important limitations of existing independence-based algorithms. These algorithms proceed by performing statistical independence tests on data, trusting completely the outcome of each test. In practice tests may be incorrect, resulting in potential cascading errors and the consequent reduction in the quality of the structures learned. IBMAP contemplates this uncertainty in the outcome of the tests through a probabilistic maximum-a-posteriori approach. The approach is instantiated in the IBMAP-HC algorithm, a structure selection strategy that performs a polynomial heuristic local search in the space of possible structures. We present an extensive empirical evaluation on synthetic and real data, showing that our algorithm outperforms significantly the current independence-based algorithms, in terms of data efficiency and quality of learned structures, with equivalent computational complexities. We also show the performance of IBMAP-HC in a real-world application of knowledge discovery: EDAs, which are evolutionary algorithms that use structure learning on each generation for modeling the distribution of populations. The experiments show that when IBMAP-HC is used to learn the structure, EDAs improve the convergence to the optimum

Spectral Polarization and Spectral Phase Control of Time and Energy Entangled Photons

We demonstrate a scheme to spectrally manipulate a collinear, continuous stream of time and energy entangled photons to generate beamlike, bandwidth-limited fuxes of polarization-entangled photons with nearly-degenerate wavelengths. Utilizing an ultrashort-pulse shaper to control the spectral phase and polarization of the photon pairs, we tailor the shape of the Hong-Ou-Mandel interference pattern, demonstrating the rules that govern the dependence of this interference pattern on the spectral phases of the photons. We then use the pulse shaper to generate all four polarization Bell states. The singlet state generated by this scheme forms a very robust decoherence-free subspace, extremely suitable for long distance fiber-optics based quantum communication.Comment: 5 pages, 3 figure

Regulating Financial Planners: Assessing the Current System and Some Alternatives

This chapter reviews US federal and state regulation of financial planners, and it also addresses concerns related to consumer confusion over the standards of care that planners provide and the titles, designations, and certifications that they use. We discuss the advantages and disadvantages of some alternative regulatory approaches, and conclude that an additional layer of regulation specific to financial planners may not be warranted at this time