An Attention-based Collaboration Framework for Multi-View Network Representation Learning

Learning distributed node representations in networks has been attracting increasing attention recently due to its effectiveness in a variety of applications. Existing approaches usually study networks with a single type of proximity between nodes, which defines a single view of a network. However, in reality there usually exists multiple types of proximities between nodes, yielding networks with multiple views. This paper studies learning node representations for networks with multiple views, which aims to infer robust node representations across different views. We propose a multi-view representation learning approach, which promotes the collaboration of different views and lets them vote for the robust representations. During the voting process, an attention mechanism is introduced, which enables each node to focus on the most informative views. Experimental results on real-world networks show that the proposed approach outperforms existing state-of-the-art approaches for network representation learning with a single view and other competitive approaches with multiple views.Comment: CIKM 201

Cooperation and Cluster Strategies Within and Between Technology-Intensive Organizations: How to Enhance Linkages among Firms in TechnoParks

World today is characterized by rapid transformations in all aspects of human’s life where innovation, technological change and technological progress play the most significant role. Therefore, technologyintensive organizations by engaging in strategic alliances, clusters and networks tend to extract maximum benefits i.e. to enable entry into the international markets and to develop core competences. Even though clusters have become a highly popular strategy, many of them fail to realize their intended goals. Thus, under the scope of this paper we explore why choosing a clustering strategy can be beneficial for technologyintensive organizations. Main focus will be on investigating if there are inter-firm and firm-university linkages among the actors located in a particular techno-park i.e. METU Techno-park and Bilkent Cyber-park. Results of the analysis showed certain extent of firm-university relationships and low level of inter-firm interactions. This further implied necessity of the policy interventions for enhancement of those interactions if the studied techno-parks are to become successful in the sense of the theoretical techno-park model, and if the tenant firms are to extract maximum benefits associated with cluster concept in theory.Clusters, Networks, Innovation, Techno-parks, Policy

Laboratory Experiments in Political Economy

Most of the laboratory research in political science follows the style that was pioneered in experimental economics a half-century ago by Vernon Smith. The connection between this style of political science experimentation and economics experimentation parallels the connection between economic theory and formal political theory.

Unsupervised Domain Adaptation using Graph Transduction Games

Unsupervised domain adaptation (UDA) amounts to assigning class labels to the unlabeled instances of a dataset from a target domain, using labeled instances of a dataset from a related source domain. In this paper, we propose to cast this problem in a game-theoretic setting as a non-cooperative game and introduce a fully automatized iterative algorithm for UDA based on graph transduction games (GTG). The main advantages of this approach are its principled foundation, guaranteed termination of the iterative algorithms to a Nash equilibrium (which corresponds to a consistent labeling condition) and soft labels quantifying the uncertainty of the label assignment process. We also investigate the beneficial effect of using pseudo-labels from linear classifiers to initialize the iterative process. The performance of the resulting methods is assessed on publicly available object recognition benchmark datasets involving both shallow and deep features. Results of experiments demonstrate the suitability of the proposed game-theoretic approach for solving UDA tasks.Comment: Oral IJCNN 201