An Empirical Study of Factors Affecting Language-Independent Models

Scaling existing applications and solutions to multiple human languages has traditionally proven to be difficult, mainly due to the language-dependent nature of preprocessing and feature engineering techniques employed in traditional approaches. In this work, we empirically investigate the factors affecting language-independent models built with multilingual representations, including task type, language set and data resource. On two most representative Natural Language Processing tasks --- sentence classification and sequence labeling, we show that language-independent models can be comparable to or even outperforms the models trained using monolingual data, and they are generally more effective on sentence classification. We experiment language-independent models with many different languages and show that they are more suitable for typologically similar languages. We also explore the effects of different data sizes when training and testing language-independent models, and demonstrate that they are not only suitable for high-resource languages, but also very effective in low-resource languages

Measurement-efficient quantum Krylov subspace diagonalisation

The Krylov subspace methods, being one category of the most important classical numerical methods for linear algebra problems, their quantum generalisation can be much more powerful. However, quantum Krylov subspace algorithms are prone to errors due to inevitable statistical fluctuations in quantum measurements. To address this problem, we develop a general theoretical framework to analyse the statistical error and measurement cost. Based on the framework, we propose a quantum algorithm to construct the Hamiltonian-power Krylov subspace that can minimise the measurement cost. In our algorithm, the product of power and Gaussian functions of the Hamiltonian is expressed as an integral of the real-time evolution, such that it can be evaluated on a quantum computer. We compare our algorithm with other established quantum Krylov subspace algorithms in solving two prominent examples. It is shown that the measurement number in our algorithm is typically $10^4$ to $10^{12}$ times smaller than other algorithms. Such an improvement can be attributed to the reduced cost of composing projectors onto the ground state. These results show that our algorithm is exceptionally robust to statistical fluctuations and promising for practical applications.Comment: 18 pages, 5 figure

Fostering User Engagement: Rhetorical Devices for Applause Generation Learnt from TED Talks

One problem that every presenter faces when delivering a public discourse is how to hold the listeners' attentions or to keep them involved. Therefore, many studies in conversation analysis work on this issue and suggest qualitatively con-structions that can effectively lead to audience's applause. To investigate these proposals quantitatively, in this study we an-alyze the transcripts of 2,135 TED Talks, with a particular fo-cus on the rhetorical devices that are used by the presenters for applause elicitation. Through conducting regression anal-ysis, we identify and interpret 24 rhetorical devices as triggers of audience applauding. We further build models that can rec-ognize applause-evoking sentences and conclude this work with potential implications

Crowdfunding platforms and the design of paying publics

Crowdfunding enables groups to self-fund the changes they want to make in the world. In other words, digital financial platforms are proving capable of supporting new relations between groups of people as well as offering new ways to organize money. Taking an HCI lens, we look at how some crowdfunding platform owners are approaching social innovation, not only at the level of supporting individual community initiatives, but at the broader level of using their platform to change societal behavior. Through four case studies, we show how crowdfunding has been chosen as a tool to redesign society by promoting environmental or social sustainability. We argue that the groups constituted through these interactions are not merely ‘crowds’, but deliberate constellations built round a thing of interest (or ‘paying publics’). Our interviews with managers and owners explore how interactions with and around platforms work to achieve these ends and we conclude with design considerations