Model reductions for inference: generality of pairwise, binary, and planar factor graphs.

We offer a solution to the problem of efficiently translating algorithms between different types of discrete statistical model. We investigate the expressive power of three classes of model-those with binary variables, with pairwise factors, and with planar topology-as well as their four intersections. We formalize a notion of "simple reduction" for the problem of inferring marginal probabilities and consider whether it is possible to "simply reduce" marginal inference from general discrete factor graphs to factor graphs in each of these seven subclasses. We characterize the reducibility of each class, showing in particular that the class of binary pairwise factor graphs is able to simply reduce only positive models. We also exhibit a continuous "spectral reduction" based on polynomial interpolation, which overcomes this limitation. Experiments assess the performance of standard approximate inference algorithms on the outputs of our reductions.

Neural mechanisms of belief inference during cooperative games.

Humans have the arguably unique ability to understand the mental representations of others. For success in both competitive and cooperative interactions, however, this ability must be extended to include representations of others' belief about our intentions, their model about our belief about their intentions, and so on. We developed a "stag hunt" game in which human subjects interacted with a computerized agent using different degrees of sophistication (recursive inferences) and applied an ecologically valid computational model of dynamic belief inference. We show that rostral medial prefrontal (paracingulate) cortex, a brain region consistently identified in psychological tasks requiring mentalizing, has a specific role in encoding the uncertainty of inference about the other's strategy. In contrast, dorsolateral prefrontal cortex encodes the depth of recursion of the strategy being used, an index of executive sophistication. These findings reveal putative computational representations within prefrontal cortex regions, supporting the maintenance of cooperation in complex social decision making.

Rebuilding the limit order book: Sequential Bayesian inference on hidden states

The limit order book of an exchange represents an information store of market participants' future aims and for many traders the information held in this store is of interest. However, information loss occurs between orders being entered into the exchange and limit order book data being sent out. We present an online algorithm which carries out Bayesian inference to replace information lost at the level of the exchange server and apply our proof of concept algorithm to real historical data from some of the world's most liquid futures contracts as traded on CME GLOBEX, EUREX and NYSE Liffe exchanges. © 2013 © 2013 Taylor & Francis.

4-channel polymeric optical bus module for board-level optical interconnections

A 4-channel polymeric optical bus module suitable for use in board-levelinterconnections is presented. Low-loss and low-crosstalk module performance is achieved, while-1 dB alignment tolerances better than ± 8 μm are demonstrated. © OSA 2012.

Utility of ITS1-5.8S-ITS2 sequences for species discrimination and phylogenetic inference of two closely related bucephalid digeneans (Digenea : Bucephalidae): Dollfustrema vaneyi and Dollfustrema hefeiensis

The complete internal transcribed spacer 1 (ITS1), 5.8S ribosomal DNA, and ITS2 region of the ribosomal DNA from 60 specimens belonging to two closely related bucephalid digeneans (Dollfustrema vaneyi and Dollfustrema hefeiensis) from different localities, hosts, and microhabitat sites were cloned to examine the level of sequence variation and the taxonomic levels to show utility in species identification and phylogeny estimation. Our data show that these molecular markers can help to discriminate the two species, which are morphologically very close and difficult to separate by classical methods. We found 21 haplotypes defined by 44 polymorphic positions in 38 individuals of D. vaneyi, and 16 haplotypes defined by 43 polymorphic positions in 22 individuals of D. hefeiensis. There is no shared haplotypes between the two species. Haplotype rather than nucleotide diversity is similar between the two species. Phylogenetic analyses reveal two robustly supported clades, one corresponding to D. vaneyi and the other corresponding to D. hefeiensis. However, the population structures between the two species seem to be incongruent and show no geographic and host-specific structure among them, further indicating that the two species may have had a more complex evolutionary history than expected.

Semantic transform: Weakly supervised semantic inference for relating visual attributes

Relative (comparative) attributes are promising for thematic ranking of visual entities, which also aids in recognition tasks. However, attribute rank learning often requires a substantial amount of relational supervision, which is highly tedious, and apparently impractical for real-world applications. In this paper, we introduce the Semantic Transform, which under minimal supervision, adaptively finds a semantic feature space along with a class ordering that is related in the best possible way. Such a semantic space is found for every attribute category. To relate the classes under weak supervision, the class ordering needs to be refined according to a cost function in an iterative procedure. This problem is ideally NP-hard, and we thus propose a constrained search tree formulation for the same. Driven by the adaptive semantic feature space representation, our model achieves the best results to date for all of the tasks of relative, absolute and zero-shot classification on two popular datasets. © 2013 IEEE.

Bayesian inference and learning in Gaussian process state-space models with Particle MCMC

State-space models are successfully used in many areas of science, engineering and economics to model time series and dynamical systems. We present a fully Bayesian approach to inference and learning (i.e. state estimation and system identification) in nonlinear nonparametric state-space models. We place a Gaussian process prior over the state transition dynamics, resulting in a flexible model able to capture complex dynamical phenomena. To enable efficient inference, we marginalize over the transition dynamics function and, instead, infer directly the joint smoothing distribution using specially tailored Particle Markov Chain Monte Carlo samplers. Once a sample from the smoothing distribution is computed, the state transition predictive distribution can be formulated analytically. Our approach preserves the full nonparametric expressivity of the model and can make use of sparse Gaussian processes to greatly reduce computational complexity.

White light emission from fiber pigtailed laser module

We fabricated a phosphor-conversion white light using an InGaN laser diode that emits 445 nm and phosphor that emit in the yellow. The InGaN laser diode was coupled to an optical fiber firstly and the phosphor was excited by the laser light output from the fiber. At 350 mA injection current the luminous flux and the luminous efficacy was 73 lm and 42.7 lm/W, respectively. The luminance was estimated to be 50 cd/mm(2). The relationship of the luminous flux and the luminous efficacy of the white light with injection current were measured and discussed.

Silicon-on-insulator thermo-optic variable attenuator module with fast response

A thermo-optic variable optical attenuator module composed of a silicon-on-insulator attenuator chip and driving circuit was designed and fabricated. The module exhibited a maximum attenuation of 21.8 dB and a response time of 10 mu s. (c) 2005 Society of Photo-Optical Instrumentation Engineers.

10 Gbit s(-1) electroabsorption-modulated laser light-source module using selective area MOVPE

A distributed-feedback (DFB) laser and a high-speed electroabsorption (EA) modulator are integrated, on the basis of the selective area MOVPE growth (SAG) technique and the ridge waveguide structure, for a 10 Gbit s(-1) optical transmission system. The integrated DFB laser/EA modulator device is packaged in a compact module with a 20% optical coupling efficiency to the single-mode fibre. The typical threshold current is 15 mA, and the side-mode suppression ratio is over 40 dB with the single-mode operation at 1550 nm. The module exhibits 1.2 mW fibre output power at a laser gain current of 70 mA and a modulator bias voltage of 0 V. The 3 dB bandwidth is 12 GHz. A dynamic extinction ratio of over 10 dB has been successfully achieved under 10 Gbit s(-1) non-return to zero (NRZ) operation, and a clearly open eye diagram is obtained.