Light Spanners

A $t$-spanner of a weighted undirected graph $G=(V,E)$, is a subgraph $H$ such that $d_H(u,v)\le t\cdot d_G(u,v)$ for all $u,v\in V$. The sparseness of the spanner can be measured by its size (the number of edges) and weight (the sum of all edge weights), both being important measures of the spanner's quality -- in this work we focus on the latter. Specifically, it is shown that for any parameters $k\ge 1$ and $\epsilon>0$, any weighted graph $G$ on $n$ vertices admits a $(2k-1)\cdot(1+\epsilon)$-stretch spanner of weight at most $w(MST(G))\cdot O_\epsilon(kn^{1/k}/\log k)$, where $w(MST(G))$ is the weight of a minimum spanning tree of $G$. Our result is obtained via a novel analysis of the classic greedy algorithm, and improves previous work by a factor of $O(\log k)$.Comment: 10 pages, 1 figure, to appear in ICALP 201

ε\varepsilon-Coresets for Clustering (with Outliers) in Doubling Metrics

We study the problem of constructing $\varepsilon$-coresets for the $(k, z)$-clustering problem in a doubling metric $M(X, d)$. An $\varepsilon$-coreset is a weighted subset $S\subseteq X$ with weight function $w : S \rightarrow \mathbb{R}_{\geq 0}$, such that for any $k$-subset $C \in [X]^k$, it holds that $\sum_{x \in S}{w(x) \cdot d^z(x, C)} \in (1 \pm \varepsilon) \cdot \sum_{x \in X}{d^z(x, C)}$. We present an efficient algorithm that constructs an $\varepsilon$-coreset for the $(k, z)$-clustering problem in $M(X, d)$, where the size of the coreset only depends on the parameters $k, z, \varepsilon$ and the doubling dimension $\mathsf{ddim}(M)$. To the best of our knowledge, this is the first efficient $\varepsilon$-coreset construction of size independent of $|X|$ for general clustering problems in doubling metrics. To this end, we establish the first relation between the doubling dimension of $M(X, d)$ and the shattering dimension (or VC-dimension) of the range space induced by the distance $d$. Such a relation was not known before, since one can easily construct instances in which neither one can be bounded by (some function of) the other. Surprisingly, we show that if we allow a small $(1\pm\epsilon)$-distortion of the distance function $d$, and consider the notion of $\tau$-error probabilistic shattering dimension, we can prove an upper bound of $O( \mathsf{ddim}(M)\cdot \log(1/\varepsilon) +\log\log{\frac{1}{\tau}} )$ for the probabilistic shattering dimension for even weighted doubling metrics. We believe this new relation is of independent interest and may find other applications. We also study the robust coresets and centroid sets in doubling metrics. Our robust coreset construction leads to new results in clustering and property testing, and the centroid sets can be used to accelerate the local search algorithms for clustering problems.Comment: Appeared in FOCS 2018, this is the full versio

Knowledge production and disciplinary practices in a British University: A qualitative cross-disciplinary case study

Knowledge is a controversial matter in UK Higher Education (HE). The increasing regulation of universities’ research focus and outputs, and the balance of applied and pure research are highly contested. Funders and government call increasingly for research that is co-produced with non-academic partners, and that demonstrates impact beyond HE. Many academics also support these calls. Yet at grass-roots level, there are epistemological tensions such as researchers’ rights to academic freedom. Moreover, there is a lack of literature exploring current research practices from a cross-disciplinary perspective. This cross-sectional, qualitative case study aimed to explore researchers’ experiences to understand if, why and how, these pressures have changed disciplinary working practices and knowledge types, and what researchers think of these changes. The study took place in one research-intensive UK University using group interviews in four disciplinary areas. Data was analysed at a semantic level, using thematic analysis. The theoretical lens of “social realism” provided a philosophical basis to the research and aided understanding of the data. Researchers reported changes to working practices because of emphasis on research relevance, technological advances and pressures to work across disciplines. There was a broadening of knowledge types and a simultaneous narrowing of research topics in some disciplinary areas. Depending on the types of knowledge they worked with, researchers had different perspectives on peer-review, the right to absolute academic freedom and newer forms of research evaluation. There were differences in the data relating to discipline and academic rank. The conclusions advocate a social realist position, with four recommendations: maintenance of impact in the REF and the introduction and monitoring of the effect of “responsible metrics” to protect disciplinary research; the tailoring of professional learning opportunities regarding research practice to disciplinary contexts; future research in relation to Basil Bernstein’s work on the trajectory of singular and regional knowledge forms

‘Working for nothing?’ : how do students and graduates utilise unpaid work for career mobilities?

A degree is no longer enough to guarantee graduate career success, so work experience increasingly provides a way to meet requirements of graduate employers. Such experience is often unpaid in the form of internships, work experience and volunteering. In a neoliberal culture that promotes individual agency and responsibility, education and hard work are often regarded as the keys to success. However, many such opportunities are unpaid, low paid or are created by personal and family contacts, all of which can further disadvantage individuals with less social, cultural and economic capitals. New graduates in 2016 accrued an average debt of £44,500 plus interest and faced strong competition in the labour market due to the record numbers of graduates and insufficient appropriate vacancies. Whilst paying for a degree may represent a sound investment in increasing future earnings this is not evenly the case.Through qualitative analysis of semi-structured interviews this research sought to understand the nature of unpaid work and career mobility experiences of students and graduates within a complex and changing context. It found that, for many, unpaid work forms an integral part of their lives. Mobility experiences such as international placements, volunteering and internships were important opportunities to develop career capitals. Pressures of study, work and family commitments posed a barrier and funded opportunities were highly valuable in widening participation.The study found that unpaid career and mobility experiences significantly helped participants to gain tangible benefits and develop soft skills which made them more able to achieve successful outcomes, regardless of background and university attended. However, such opportunities magnified existing inequalities as young people starting with higher career capitals (e.g. parents with money and contacts) were able to access more valuable opportunities earlier. Unique contributions to the field were a typology of different forms of unpaid work experienced by students, a focus on the ‘middle-band’ (not just the highest achievers or most disadvantaged), application of interpretive phenomenology to careers research and a proposed new dimension of the concept of ‘boundaryless careers.

A Design Science Research Approach to Smart and Collaborative Urban Supply Networks

Urban supply networks are facing increasing demands and challenges and thus constitute a relevant field for research and practical development. Supply chain management holds enormous potential and relevance for society and everyday life as the flow of goods and information are important economic functions. Being a heterogeneous field, the literature base of supply chain management research is difficult to manage and navigate. Disruptive digital technologies and the implementation of cross-network information analysis and sharing drive the need for new organisational and technological approaches. Practical issues are manifold and include mega trends such as digital transformation, urbanisation, and environmental awareness. A promising approach to solving these problems is the realisation of smart and collaborative supply networks. The growth of artificial intelligence applications in recent years has led to a wide range of applications in a variety of domains. However, the potential of artificial intelligence utilisation in supply chain management has not yet been fully exploited. Similarly, value creation increasingly takes place in networked value creation cycles that have become continuously more collaborative, complex, and dynamic as interactions in business processes involving information technologies have become more intense. Following a design science research approach this cumulative thesis comprises the development and discussion of four artefacts for the analysis and advancement of smart and collaborative urban supply networks. This thesis aims to highlight the potential of artificial intelligence-based supply networks, to advance data-driven inter-organisational collaboration, and to improve last mile supply network sustainability. Based on thorough machine learning and systematic literature reviews, reference and system dynamics modelling, simulation, and qualitative empirical research, the artefacts provide a valuable contribution to research and practice