Generalization Bounds for Representative Domain Adaptation

In this paper, we propose a novel framework to analyze the theoretical properties of the learning process for a representative type of domain adaptation, which combines data from multiple sources and one target (or briefly called representative domain adaptation). In particular, we use the integral probability metric to measure the difference between the distributions of two domains and meanwhile compare it with the H-divergence and the discrepancy distance. We develop the Hoeffding-type, the Bennett-type and the McDiarmid-type deviation inequalities for multiple domains respectively, and then present the symmetrization inequality for representative domain adaptation. Next, we use the derived inequalities to obtain the Hoeffding-type and the Bennett-type generalization bounds respectively, both of which are based on the uniform entropy number. Moreover, we present the generalization bounds based on the Rademacher complexity. Finally, we analyze the asymptotic convergence and the rate of convergence of the learning process for representative domain adaptation. We discuss the factors that affect the asymptotic behavior of the learning process and the numerical experiments support our theoretical findings as well. Meanwhile, we give a comparison with the existing results of domain adaptation and the classical results under the same-distribution assumption.Comment: arXiv admin note: substantial text overlap with arXiv:1304.157

Orientation dependence of the optical spectra in graphene at high frequencies

On the basis of the Kubo formula we evaluated the optical conductivity of a graphene sheet. The full behavior of frequency as well as temperature dependence of the optical conductivity is presented. We show that the anisotropy of conductivity can be significantly enhanced at high frequencies. The photon absorption depends on the field polarization direction. At the frequency comparable to the maximum separation of upper and lower bands the photon-induced conduction of electrons is strongly suppressed if the polarization of field is along the zigzag direction. The corresponding optical conductivity is several orders of magnitude weaker than that when the light is polarizing along the armchair direction. We propose that the property of orientation selection of absorption in the graphene can be used as a basis for a high-frequency partial polarizer.Comment: 5 pages, 5 figure

Network Topologies That Can Achieve Dual Function of Adaptation and Noise Attenuation.

Many signaling systems execute adaptation under circumstances that require noise attenuation. Here, we identify an intrinsic trade-off existing between sensitivity and noise attenuation in the three-node networks. We demonstrate that although fine-tuning timescales in three-node adaptive networks can partially mediate this trade-off in this context, it prolongs adaptation time and imposes unrealistic parameter constraints. By contrast, four-node networks can effectively decouple adaptation and noise attenuation to achieve dual function without a trade-off, provided that these functions are executed sequentially. We illustrate ideas in seven biological examples, including Dictyostelium discoideum chemotaxis and the p53 signaling network and find that adaptive networks are often associated with a noise attenuation module. Our approach may be applicable to finding network design principles for other dual and multiple functions