5,763 research outputs found
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
Estimates of DI Hydrous Ethanol Utilization for Knock Avoidance and Comparison to a Measured and Simulated DI E85 Baseline
Evaluation of turbo-Brayton cycle for cooling current leads: Integrated current lead/heat exchanger
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
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