Approximate Bayesian Computation for Smoothing

We consider a method for approximate inference in hidden Markov models (HMMs). The method circumvents the need to evaluate conditional densities of observations given the hidden states. It may be considered an instance of Approximate Bayesian Computation (ABC) and it involves the introduction of auxiliary variables valued in the same space as the observations. The quality of the approximation may be controlled to arbitrary precision through a parameter ε > 0. We provide theoretical results which quantify, in terms of ε, the ABC error in approximation of expectations of additive functionals with respect to the smoothing distributions. Under regularity assumptions, this error is, where n is the number of time steps over which smoothing is performed. For numerical implementation, we adopt the forward-only sequential Monte Carlo (SMC) scheme of [14] and quantify the combined error from the ABC and SMC approximations. This forms some of the first quantitative results for ABC methods which jointly treat the ABC and simulation errors, with a finite number of data and simulated samples. © Taylor & Francis Group, LLC.

Transparent oxide semiconductors for advanced display applications

The article discusses the progress and issues related to transparent oxide semiconductor (TOS) TFTs for advanced display and imaging applications. Amorphous oxide semiconductors continue to spark new technological developments in transparent electronics on a multitude of non-conventional substrates. Applications range from high-frame-rate interactive displays with embedded imaging to flexible electronics, where speed and transparency are essential requirements. TOS TFTs exhibit high transparency as well as high electron mobility even when fabricated at room temperature. Compared to conventional a-Si TFT technology, TOS TFTs have higher mobility and sufficiently good uniformity over large areas, similar in many ways to LTPS TFTs. Moreover, because the amorphous oxide semiconductor has higher mobility compared to that of conventional a-Si TFT technology, this allows higher-frame-rate display operation. This would greatly benefit OLED displays in particular because of the need for lower-cost higher-mobility analog circuits at every subpixel.

N-gram posterior probability confidence measures for statistical machine translation: An empirical study

We report an empirical study of n-gram posterior probability confidence measures for statistical machine translation (SMT). We first describe an efficient and practical algorithm for rapidly computing n-gram posterior probabilities from large translation word lattices. These probabilities are shown to be a good predictor of whether or not the n-gram is found in human reference translations, motivating their use as a confidence measure for SMT. Comprehensive n-gram precision and word coverage measurements are presented for a variety of different language pairs, domains and conditions. We analyze the effect on reference precision of using single or multiple references, and compare the precision of posteriors computed from k-best lists to those computed over the full evidence space of the lattice. We also demonstrate improved confidence by combining multiple lattices in a multi-source translation framework. © 2012 The Author(s).