Probabilistic Sparse Subspace Clustering Using Delayed Association

Discovering and clustering subspaces in high-dimensional data is a fundamental problem of machine learning with a wide range of applications in data mining, computer vision, and pattern recognition. Earlier methods divided the problem into two separate stages of finding the similarity matrix and finding clusters. Similar to some recent works, we integrate these two steps using a joint optimization approach. We make the following contributions: (i) we estimate the reliability of the cluster assignment for each point before assigning a point to a subspace. We group the data points into two groups of "certain" and "uncertain", with the assignment of latter group delayed until their subspace association certainty improves. (ii) We demonstrate that delayed association is better suited for clustering subspaces that have ambiguities, i.e. when subspaces intersect or data are contaminated with outliers/noise. (iii) We demonstrate experimentally that such delayed probabilistic association leads to a more accurate self-representation and final clusters. The proposed method has higher accuracy both for points that exclusively lie in one subspace, and those that are on the intersection of subspaces. (iv) We show that delayed association leads to huge reduction of computational cost, since it allows for incremental spectral clustering

Seeking the Global Generation:A Comparative Case Study of Youth from Canada, Georgia, and Saudi

This study explores how contemporary youth understand their lives under today’s context of globalization. It examines and compares perceptions and practice of high school age (15-18 years old) students from Canada, Georgia, and Saudi; how they think about the world and their place in it, and how they take up their roles as citizens of their local, national, and global communities. The study investigates if there are bases to collectively address these youth as a ‘Global Generation.’ By illuminating the core features of this generation it expounds on the implications of the existence of the Global Generation in relation to the hopes of an emerging ‘one-world’ vision. This study uses qualitative inquiry based on interpretive paradigm, employing a comparative case study (CCS) methodology, with multiple research techniques: e-survey (n=79), individual interviews (n=21), and experiential activities (n=21). Using Biesta’s approach to citizenship learning (CL) as a theoretical framework, allows for the consideration of the interplay between young people’s dispositions, relationships, and contexts in everyday settings, in order toreveal the multidimensional nature of the lives of youth in their particular and broader contexts, including their citizenship learning. The findings demonstrate that today’s global youth share similar attitudes, understandings, aspirations, and anxieties. They are well informed, skilled in modern technologies, self-reliant, and competitive. They have multiple belongings and identifications, are inclusive of other youth and cultures, have cosmopolitan dispositions, and reject the binary of the concepts ‘local’ and ‘global.’ They consider open-mindedness, tolerance, and solidarity as essential qualities to promote international connections, but foremost, identify ‘common humanity’ as the underlying and binding force of humankind. While being vernacular cosmopolitans youth struggle to apply their values to the world. They lack knowledge and skills to be involved in social movements, and do not see themselves capable of promoting any systemic change, but rather entrusting decision-making to the authorities. Due to the multiple similarities found among the participants’ ways of doing and being, the study proposes that today’s youth, relationally bound together with technological mediation, can be conceptualised as the Global Generation whose characteristics transcend many national, ethnic, religious, gender, and socio-economic borders

Computing 22-twinless blocks

Let $G=(V,E))$ be a directed graph. A $2$-twinless block in $G$ is a maximal vertex set $B\subseteq V$ of size at least $2$ such that for each pair of distinct vertices $x,y \in B$, and for each vertex $w\in V\setminus\left\lbrace x,y \right\rbrace$, the vertices $x,y$ are in the same twinless strongly connected component of $G\setminus\left \lbrace w \right\rbrace$. In this paper we present algorithms for computing the $2$-twinless blocks of a directed graph