An Online Expectation-Maximization Algorithm for Changepoint Models

Changepoint models are widely used to model the heterogeneity of sequential data. We present a novel sequential Monte Carlo (SMC) online Expectation-Maximization (EM) algorithm for estimating the static parameters of such models. The SMC online EM algorithm has a cost per time which is linear in the number of particles and could be particularly important when the data is representable as a long sequence of observations, since it drastically reduces the computational requirements for implementation. We present an asymptotic analysis for the stability of the SMC estimates used in the online EM algorithm and demonstrate the performance of this scheme using both simulated and real data originating from DNA analysis.

Copula-based Kernel Dependency Measures

The paper presents a new copula based method for measuring dependence between random variables. Our approach extends the Maximum Mean Discrepancy to the copula of the joint distribution. We prove that this approach has several advantageous properties. Similarly to Shannon mutual information, the proposed dependence measure is invariant to any strictly increasing transformation of the marginal variables. This is important in many applications, for example in feature selection. The estimator is consistent, robust to outliers, and uses rank statistics only. We derive upper bounds on the convergence rate and propose independence tests too. We illustrate the theoretical contributions through a series of experiments in feature selection and low-dimensional embedding of distributions.

Forecasting high-frequency futures returns using online langevin dynamics

Forecasting the returns of assets at high frequency is the key challenge for high-frequency algorithmic trading strategies. In this paper, we propose a jump-diffusion model for asset price movements that models price and its trend and allows a momentum strategy to be developed. Conditional on jump times, we derive closed-form transition densities for this model. We show how this allows us to extract a trend from high-frequency finance data by using a Rao-Blackwellized variable rate particle filter to filter incoming price data. Our results show that even in the presence of transaction costs our algorithm can achieve a Sharpe ratio above 1 when applied across a portfolio of 75 futures contracts at high frequency. © 2011 IEEE.

Integrated online speaker clustering and adaptation

For many applications, it is necessary to produce speech transcriptions in a causal fashion. To produce high quality transcripts, speaker adaptation is often used. This requires online speaker clustering and incremental adaptation techniques to be developed. This paper presents an integrated approach to online speaker clustering and adaptation which allows efficient clustering of speakers using the same accumulated statistics that are normally used for adaptation. Using a consistent criterion for both clustering and adaptation should yield gains for both stages. The proposed approach is evaluated on a meetings transcription task using audio from multiple distant microphones. Consistent gains over standard clustering and adaptation were obtained. Copyright © 2011 ISCA.

An online expectation-maximisation algorithm for nonnegative matrix factorisation models

In this paper we formulate the nonnegative matrix factorisation (NMF) problem as a maximum likelihood estimation problem for hidden Markov models and propose online expectation-maximisation (EM) algorithms to estimate the NMF and the other unknown static parameters. We also propose a sequential Monte Carlo approximation of our online EM algorithm. We show the performance of the proposed method with two numerical examples. © 2012 IFAC.

IPLR: An online resource for Greek word-level and sublexical information

We present a new online psycholinguistic resource for Greek based on analyses of written corpora combined with text processing technologies developed at the Institute for Language & Speech Processing (ILSP), Greece. The "ILSP PsychoLinguistic Resource" (IPLR) is a freely accessible service via a dedicated web page, at http://speech.ilsp.gr/iplr. IPLR provides analyses of user-submitted letter strings (words and nonwords) as well as frequency tables for important units and conditions such as syllables, bigrams, and neighbors, calculated over two word lists based on printed text corpora and their phonetic transcription. Online tools allow retrieval of words matching user-specified orthographic or phonetic patterns. All results and processing code (in the Python programming language) are freely available for noncommercial educational or research use. © 2010 Springer Science+Business Media B.V.

Closing the Energy Efficiency Gap: A study linking demographics with barriers to adopting energy efficiency measures in the home

This paper presents a study which linked demographic variables with barriers affecting the adoption of domestic energy efficiency measures in large UK cities. The aim was to better understand the 'Energy Efficiency Gap' and improve the effectiveness of future energy efficiency initiatives. The data for this study was collected from 198 general population interviews (1.5-10 min) carried out across multiple locations in Manchester and Cardiff. The demographic variables were statistically linked to the identified barriers using a modified chi-square test of association (first order Rao-Scott corrected to compensate for multiple response data), and the effect size was estimated with an odds-ratio test. The results revealed that strong associations exist between demographics and barriers, specifically for the following variables: sex; marital status; education level; type of dwelling; number of occupants in household; residence (rent/own); and location (Manchester/Cardiff). The results and recommendations were aimed at city policy makers, local councils, and members of the construction/retrofit industry who are all working to improve the energy efficiency of the domestic built environment. © 2012 Elsevier Ltd.

Ventilation effectiveness measures based on heat removal: Part 2. Application to natural ventilation flows

The three effectiveness measures based on the ability of a flow to flush buoyancy from a ventilated space proposed by Coffey and Hunt [Ventilation effectiveness measures based on heat removal-part 1. Definitions. Building and Environment, in press, doi:10.1016/j.buildenv.2006.03.016.] are applied to assess and compare two fundamental natural ventilation flows. We focus on the limiting cases of passive displacement and passive mixing ventilation flows during transient conditions. These transient flows occur when, for example, heat is purged from a building at night. Whilst it is widely recognised that mixing flows are less efficient at purging heat than displacement flows, our results indicate that, when a particular zone of a room is considered, displacement ventilation can result in lower effectiveness than mixing ventilation. When a room is considered as a whole, displacement ventilation yields higher effectiveness than mixing ventilation and we quantify these differences in terms of the geometry of the space and opening area. The proposed theoretical predictions are compared with effectiveness deduced from measurements made during laboratory experiments and show good agreement. © 2006 Elsevier Ltd. All rights reserved.

Ventilation effectiveness measures based on heat removal: Part 1. Definitions

The effectiveness of ventilation flows is considered from the perspective of buoyancy (or heat) removal from a space. This perspective is distinct from the standard in which the effectiveness is based on the concentrations of a neutrally buoyant contaminant/passive tracer. Three new measures of effectiveness are proposed based on the ability of a flow to flush buoyancy from a ventilated space. These measures provide estimates of instantaneous and time-averaged effectiveness for the entire space, and local effectiveness at any height of interest. From a generalisation of the latter, a vertical profile of effectiveness is defined. These measures enable quantitative comparisons to be made between different flows and they are applicable when there is a difference in density (as is typical due to temperature differences) between the interior environment and the replacement air. Applications, therefore, include natural ventilation, hybrid ventilation and a range of forced ventilation flows. Finally, we demonstrate how the ventilation effectiveness of a room may be assessed from simple traces of temperature versus time. © 2006 Elsevier Ltd. All rights reserved.

New ventilation efficiency measures based on buoyancy removal

New measures for estimating the efficiency of transient ventilation flows are proposed. These measures are developed by considering how effectively a ventilation system removes buoyancy from a space. This approach is distinct from standard efficiency measures which are, in general, based on the removal of a neutrally-buoyant passive tracer. Our new measures, based on (active) buoyancy removal, allow both the instantaneous and time-averaged efficiency of the entire space, or of any region within it, to be determined. In addition, expressions for determining vertical profiles of efficiency are proposed. These new measures enable the effectiveness of different flows to be compared directly and are applicable providing density (temperature) differences exist between the interior environment and the replacement air. Thus, they may be used to contrast the effectiveness of a broad range of building ventilation flows including natural, hybrid and forced ventilation.

How can online schedules improve communication and estimation tradeoff?

We consider remote state estimation and investigate the tradeoff between the sensor-to-estimator communication rate and the remote estimation quality. It is well known that if the communication rate is one, e.g., the sensor communicates with the remote estimator at each time, then the remote estimation quality is the best. It degrades when the communication rate drops. We present one optimal offline schedule and two online schedules and show that the two online schedules provide better tradeoff between the communication rate and the estimation quality than the optimal offline schedule. Simulation examples demonstrate that significant communication savings can be achieved under the two online schedules which only introduce small increment of the estimation errors. © 1991-2012 IEEE.

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).