Learning with noise and regularizers in multilayer neural networks

We study the effect of two types of noise, data noise and model noise, in an on-line gradient-descent learning scenario for general two-layer student network with an arbitrary number of hidden units. Training examples are randomly drawn input vectors labeled by a two-layer teacher network with an arbitrary number of hidden units. Data is then corrupted by Gaussian noise affecting either the output or the model itself. We examine the effect of both types of noise on the evolution of order parameters and the generalization error in various phases of the learning process.

Learning with regularizers in multilayer neural networks

We study the effect of regularization in an on-line gradient-descent learning scenario for a general two-layer student network with an arbitrary number of hidden units. Training examples are randomly drawn input vectors labelled by a two-layer teacher network with an arbitrary number of hidden units which may be corrupted by Gaussian output noise. We examine the effect of weight decay regularization on the dynamical evolution of the order parameters and generalization error in various phases of the learning process, in both noiseless and noisy scenarios.

A basis function approach to Bayesian inference in diffusion processes

In this paper, we present a framework for Bayesian inference in continuous-time diffusion processes. The new method is directly related to the recently proposed variational Gaussian Process approximation (VGPA) approach to Bayesian smoothing of partially observed diffusions. By adopting a basis function expansion (BF-VGPA), both the time-dependent control parameters of the approximate GP process and its moment equations are projected onto a lower-dimensional subspace. This allows us both to reduce the computational complexity and to eliminate the time discretisation used in the previous algorithm. The new algorithm is tested on an Ornstein-Uhlenbeck process. Our preliminary results show that BF-VGPA algorithm provides a reasonably accurate state estimation using a small number of basis functions.

Phase transitions and memory effects in the dynamics of Boolean networks

The generating functional method is employed to investigate the synchronous dynamics of Boolean networks, providing an exact result for the system dynamics via a set of macroscopic order parameters. The topology of the networks studied and its constituent Boolean functions represent the system's quenched disorder and are sampled from a given distribution. The framework accommodates a variety of topologies and Boolean function distributions and can be used to study both the noisy and noiseless regimes; it enables one to calculate correlation functions at different times that are inaccessible via commonly used approximations. It is also used to determine conditions for the annealed approximation to be valid, explore phases of the system under different levels of noise and obtain results for models with strong memory effects, where existing approximations break down. Links between Boolean networks and general Boolean formulas are identified and results common to both system types are highlighted. © 2012 Copyright Taylor and Francis Group, LLC.

Dielectric and electro-optical properties of some cyanobiphenyl liquid-crystals

A variety of methods have been reviewed for obtaining parallel or perpendicular alignment in liquid-crystal cells. Some of these methods have been selected and developed and were used in polarised spectroscopy, dielectric and electro-optic studies. Also, novel dielectric and electro-optic cells were constructed for use over a range of temperature. Dielectric response of thin layers of E7 and E8 (eutectic mixture liquid-crystals) have been measured in the frequency range (12 Hz-100 kHz) and over a range of temperature (183-337K). Dielectric spectra were also obtained for supercooled E7 and E8 in the Hz and kHz range. When the measuring electric field was parallel to the nematic director, one loss peak (low-frequency relaxation process) was observed for E7 and for E8, that exhibits a Debye-type behaviour in the supercooled systems. When the measuring electric field was perpendicular to the nematic director, two resolved dielectric processes have been observed. The phase transitions, effective molecular polarisabilities, anisotropy of polarisabilities and order parameters of three liquid crystal homologs (5CB, 6CB, and 7CB), 60CB and three eutectic nematic mixtures E7, E8, and E607 were calculated using optical and density data measured at several temperatures. The order parameters calculated using the different methods of Vuks, Neugebauer, Saupe-Maier, and Palffy-Muhoray are nearly the same for the liquid crystals considered in the present study. Also, the interrelationship between density and refractive index and the molecular structure of these liquid crystals were established. Accurate dielectric and dipole results of a range of liquid-crystal forming molecules at several temperatures have reported. The role of the cyano-end group, biphenyl core, and flexible tail in molecular association, were investigated using the dielectric method for some molecules which have a structural relationship to the nematogens. Analysis of the dielectric data for solution of the liquid-crystals indicated a high molecular association, comparable to that observed in the nematic or isotropic phases. Electro-optic Kerr effect were investigated for some alkyl cyanobiphenyls, their nematic mixtures and the eutectic mixture liquid-crystals E7 and E8 in the isotropic phase and solution. The Kerr constant of these liquid crystals found to be very high at the nematic-isotropic transition temperatures as the molecules are expected to be highly ordered close to phase transition temperatures. Dynamic Kerr effect behaviour and transient molecular reorientation were also observed in thin layers of some alkyl cyanobiphenyls. Dichroic ratio R and order parameters of solutions containing some azo and anthraquinone dyes in the nematic solvent (E7 and E8), were investigated by the measurement of the intensity of the absorption bands in the visible region of parallel aligned samples. The effective factors on the dichroic ratio of the dyes dissolved in the nematic solvents were determined and discussed.

Dynamics of Boolean networks: an exact solution

The dynamics of Boolean networks (BN) with quenched disorder and thermal noise is studied via the generating functional method. A general formulation, suitable for BN with any distribution of Boolean functions, is developed. It provides exact solutions and insight into the evolution of order parameters and properties of the stationary states, which are inaccessible via existing methodology. We identify cases where the commonly used annealed approximation is valid and others where it breaks down. Broader links between BN and general Boolean formulas are highlighted.

The throughput order of multicast traffics with physical-layer network coding in random wireless ad hoc networks

This paper attempts to address the effectiveness of physical-layer network coding (PNC) on the throughput improvement for multi-hop multicast in random wireless ad hoc networks (WAHNs). We prove that the per session throughput order with PNC is tightly bounded as T((nvmR (n))-1) if m = O(R-2 (n)), where n is the total number of nodes, R(n) is the communication range, and m is the number of destinations for each multicast session. We also show that per-session throughput order with PNC is tight bounded as T(n-1), when m = O(R-2(n)). The results of this paper imply that PNC cannot improve the throughput order of multicast in random WAHNs, which is different from the intuition that PNC may improve the throughput order as it allows simultaneous signal access and combination.